diff --git a/logs/singularity_112883.out b/logs/singularity_112883.out
new file mode 100644
index 0000000000000000000000000000000000000000..00467f9c51d06c69ce1f99e0e47a60961de6eb38
--- /dev/null
+++ b/logs/singularity_112883.out
@@ -0,0 +1,257 @@
+2023-12-01 17:35:50.608849: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
+Using TensorFlow backend
+Namespace(data_input='imu', feature_method='minirocket', lbl_str='pss', method='ml', model='cnn1d', overwrite=0, subject=-1, test_standing=1, train_len=5, win_shift=0.2, win_size=12)
+Using pre-set data id:  0
+imu_rr_S01_id0_combi5.0-7.0-10.0-12.0-15.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---CNN1D---
+2023-12-01 17:38:14.855542: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:38:17.263710: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:38:17.263947: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+input shape:  (1440, 9996)
+x shape:  (120, 9996)
+2023-12-01 17:38:17.332217: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:38:17.332415: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:38:17.332573: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:38:33.186908: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:38:33.187141: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:38:33.187290: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:38:33.187409: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1639] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 14720 MB memory:  -> device: 0, name: Quadro RTX 5000, pci bus id: 0000:0b:00.0, compute capability: 7.5
+
+Search: Running Trial #1
+
+Value             |Best Value So Far |Hyperparameter
+2                 |2                 |n_layers
+128               |128               |filter_unit0
+64                |64                |filter_unit1
+3                 |3                 |kernel_size0
+2                 |2                 |kernel_size1
+4                 |4                 |pool_size0
+1                 |1                 |pool_size1
+2                 |2                 |stride_size0
+5                 |5                 |stride_size1
+0.1               |0.1               |dropout0
+0.3               |0.3               |dropout1
+
+Traceback (most recent call last):
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/base_tuner.py", line 270, in _try_run_and_update_trial
+    self._run_and_update_trial(trial, *fit_args, **fit_kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/base_tuner.py", line 235, in _run_and_update_trial
+    results = self.run_trial(trial, *fit_args, **fit_kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/tuner.py", line 314, in run_trial
+    obj_value = self._build_and_fit_model(trial, *args, **copied_kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/tuner.py", line 233, in _build_and_fit_model
+    results = self.hypermodel.fit(hp, model, *args, **kwargs)
+  File "/home/rqchia/projects/aria-respiration-cal/models/neuralnet.py", line 178, in fit
+    history = model.fit(x, y,
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
+    raise e.with_traceback(filtered_tb) from None
+  File "/tmp/__autograph_generated_file6lza_nho.py", line 15, in tf__train_function
+    retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
+ValueError: in user code:
+
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1338, in train_function  *
+        return step_function(self, iterator)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1322, in step_function  **
+        outputs = model.distribute_strategy.run(run_step, args=(data,))
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1303, in run_step  **
+        outputs = model.train_step(data)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1080, in train_step
+        y_pred = self(x, training=True)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
+        raise e.with_traceback(filtered_tb) from None
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/input_spec.py", line 253, in assert_input_compatibility
+        raise ValueError(
+
+    ValueError: Exception encountered when calling layer 'cnn1d' (type Sequential).
+    
+    Input 0 of layer "conv1d_0" is incompatible with the layer: expected min_ndim=3, found ndim=2. Full shape received: (32, 9996)
+    
+    Call arguments received by layer 'cnn1d' (type Sequential):
+      • inputs=tf.Tensor(shape=(32, 9996), dtype=float32)
+      • training=True
+      • mask=None
+
+

Trial 1 Complete [00h 00m 02s]
+
+Best val_loss So Far: None
+Total elapsed time: 00h 00m 02s
+
+Search: Running Trial #2
+
+Value             |Best Value So Far |Hyperparameter
+1                 |2                 |n_layers
+64                |128               |filter_unit0
+1                 |3                 |kernel_size0
+1                 |4                 |pool_size0
+2                 |2                 |stride_size0
+0.1               |0.1               |dropout0
+
+Traceback (most recent call last):
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/base_tuner.py", line 270, in _try_run_and_update_trial
+    self._run_and_update_trial(trial, *fit_args, **fit_kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/base_tuner.py", line 235, in _run_and_update_trial
+    results = self.run_trial(trial, *fit_args, **fit_kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/tuner.py", line 314, in run_trial
+    obj_value = self._build_and_fit_model(trial, *args, **copied_kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/tuner.py", line 233, in _build_and_fit_model
+    results = self.hypermodel.fit(hp, model, *args, **kwargs)
+  File "/home/rqchia/projects/aria-respiration-cal/models/neuralnet.py", line 178, in fit
+    history = model.fit(x, y,
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
+    raise e.with_traceback(filtered_tb) from None
+  File "/tmp/__autograph_generated_file6lza_nho.py", line 15, in tf__train_function
+    retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
+ValueError: in user code:
+
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1338, in train_function  *
+        return step_function(self, iterator)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1322, in step_function  **
+        outputs = model.distribute_strategy.run(run_step, args=(data,))
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1303, in run_step  **
+        outputs = model.train_step(data)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1080, in train_step
+        y_pred = self(x, training=True)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
+        raise e.with_traceback(filtered_tb) from None
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/input_spec.py", line 253, in assert_input_compatibility
+        raise ValueError(
+
+    ValueError: Exception encountered when calling layer 'cnn1d' (type Sequential).
+    
+    Input 0 of layer "conv1d_0" is incompatible with the layer: expected min_ndim=3, found ndim=2. Full shape received: (32, 9996)
+    
+    Call arguments received by layer 'cnn1d' (type Sequential):
+      • inputs=tf.Tensor(shape=(32, 9996), dtype=float32)
+      • training=True
+      • mask=None
+
+

Trial 2 Complete [00h 00m 00s]
+
+Best val_loss So Far: None
+Total elapsed time: 00h 00m 02s
+
+Search: Running Trial #3
+
+Value             |Best Value So Far |Hyperparameter
+3                 |2                 |n_layers
+64                |128               |filter_unit0
+64                |64                |filter_unit1
+32                |None              |filter_unit2
+1                 |3                 |kernel_size0
+4                 |2                 |kernel_size1
+4                 |None              |kernel_size2
+2                 |4                 |pool_size0
+5                 |1                 |pool_size1
+4                 |None              |pool_size2
+4                 |2                 |stride_size0
+1                 |5                 |stride_size1
+3                 |None              |stride_size2
+0.2               |0.1               |dropout0
+0                 |0.3               |dropout1
+0                 |None              |dropout2
+
+Traceback (most recent call last):
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/base_tuner.py", line 270, in _try_run_and_update_trial
+    self._run_and_update_trial(trial, *fit_args, **fit_kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/base_tuner.py", line 235, in _run_and_update_trial
+    results = self.run_trial(trial, *fit_args, **fit_kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/tuner.py", line 314, in run_trial
+    obj_value = self._build_and_fit_model(trial, *args, **copied_kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/tuner.py", line 233, in _build_and_fit_model
+    results = self.hypermodel.fit(hp, model, *args, **kwargs)
+  File "/home/rqchia/projects/aria-respiration-cal/models/neuralnet.py", line 178, in fit
+    history = model.fit(x, y,
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
+    raise e.with_traceback(filtered_tb) from None
+  File "/tmp/__autograph_generated_file6lza_nho.py", line 15, in tf__train_function
+    retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
+ValueError: in user code:
+
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1338, in train_function  *
+        return step_function(self, iterator)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1322, in step_function  **
+        outputs = model.distribute_strategy.run(run_step, args=(data,))
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1303, in run_step  **
+        outputs = model.train_step(data)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1080, in train_step
+        y_pred = self(x, training=True)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
+        raise e.with_traceback(filtered_tb) from None
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/input_spec.py", line 253, in assert_input_compatibility
+        raise ValueError(
+
+    ValueError: Exception encountered when calling layer 'cnn1d' (type Sequential).
+    
+    Input 0 of layer "conv1d_0" is incompatible with the layer: expected min_ndim=3, found ndim=2. Full shape received: (32, 9996)
+    
+    Call arguments received by layer 'cnn1d' (type Sequential):
+      • inputs=tf.Tensor(shape=(32, 9996), dtype=float32)
+      • training=True
+      • mask=None
+
+Traceback (most recent call last):
+  File "regress_rr.py", line 1521, in <module>
+    rr_func(subject)
+  File "regress_rr.py", line 1369, in sens_rr_model
+    transforms, model = model_training(mdl_str, x_train, y_train,
+  File "/home/rqchia/projects/aria-respiration-cal/modules/utils.py", line 260, in model_training
+    tuner.search(x_train, y_train, validation_data,
+  File "/home/rqchia/projects/aria-respiration-cal/models/neuralnet.py", line 499, in search
+    self.tuner.search(x, y, validation_data,
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/base_tuner.py", line 231, in search
+    self.on_trial_end(trial)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/base_tuner.py", line 335, in on_trial_end
+    self.oracle.end_trial(trial)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/oracle.py", line 107, in wrapped_func
+    ret_val = func(*args, **kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/oracle.py", line 429, in end_trial
+    self._check_consecutive_failures()
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/oracle.py", line 386, in _check_consecutive_failures
+    raise RuntimeError(
+RuntimeError: Number of consecutive failures exceeded the limit of 3.
+Traceback (most recent call last):
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/base_tuner.py", line 270, in _try_run_and_update_trial
+    self._run_and_update_trial(trial, *fit_args, **fit_kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/base_tuner.py", line 235, in _run_and_update_trial
+    results = self.run_trial(trial, *fit_args, **fit_kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/tuner.py", line 314, in run_trial
+    obj_value = self._build_and_fit_model(trial, *args, **copied_kwargs)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras_tuner/src/engine/tuner.py", line 233, in _build_and_fit_model
+    results = self.hypermodel.fit(hp, model, *args, **kwargs)
+  File "/home/rqchia/projects/aria-respiration-cal/models/neuralnet.py", line 178, in fit
+    history = model.fit(x, y,
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
+    raise e.with_traceback(filtered_tb) from None
+  File "/tmp/__autograph_generated_file6lza_nho.py", line 15, in tf__train_function
+    retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
+ValueError: in user code:
+
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1338, in train_function  *
+        return step_function(self, iterator)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1322, in step_function  **
+        outputs = model.distribute_strategy.run(run_step, args=(data,))
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1303, in run_step  **
+        outputs = model.train_step(data)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 1080, in train_step
+        y_pred = self(x, training=True)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
+        raise e.with_traceback(filtered_tb) from None
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/input_spec.py", line 253, in assert_input_compatibility
+        raise ValueError(
+
+    ValueError: Exception encountered when calling layer 'cnn1d' (type Sequential).
+    
+    Input 0 of layer "conv1d_0" is incompatible with the layer: expected min_ndim=3, found ndim=2. Full shape received: (32, 9996)
+    
+    Call arguments received by layer 'cnn1d' (type Sequential):
+      • inputs=tf.Tensor(shape=(32, 9996), dtype=float32)
+      • training=True
+      • mask=None
+
+
diff --git a/logs/singularity_125871.out b/logs/singularity_125871.out
new file mode 100644
index 0000000000000000000000000000000000000000..3847aad8d6110c134b251d04623582b0bbede86c
--- /dev/null
+++ b/logs/singularity_125871.out
@@ -0,0 +1,1024 @@
+2023-12-01 17:47:19.486948: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
+Using TensorFlow backend
+Namespace(data_input='imu', feature_method='None', lbl_str='pss', method='ml', model='cnn1d', overwrite=0, subject=-1, test_standing=1, train_len=5, win_shift=0.2, win_size=12)
+Using pre-set data id:  1
+imu_rr_S01_id1_combi5.0-7.0-10.0-12.0-15.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+2023-12-01 17:47:58.815959: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:47:59.153444: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:47:59.153684: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+input shape:  (1440, 6)
+x shape:  (120, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-7.0-10.0-12.0-15.0/bayesianoptimization/tuner0.json
+{'n_layers': 1, 'filter_unit0': 128, 'kernel_size0': 2, 'pool_size0': 2, 'stride_size0': 1, 'dropout0': 0.0}
+2023-12-01 17:47:59.211624: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:47:59.211829: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:47:59.211969: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:47:59.710395: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:47:59.710640: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:47:59.710784: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
+2023-12-01 17:47:59.710905: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1639] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 14720 MB memory:  -> device: 0, name: Quadro RTX 5000, pci bus id: 0000:0b:00.0, compute capability: 7.5
+2023-12-01 17:48:29.990747: I tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:432] Loaded cuDNN version 8600
+
 1/39 [..............................] - ETA: 32:04
23/39 [================>.............] - ETA: 0s   
39/39 [==============================] - 51s 3ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+QStandardPaths: XDG_RUNTIME_DIR points to non-existing path '/run/user/56779', please create it with 0700 permissions.
+imu_rr_S01_id1_combi5.0-7.0-10.0-12.0-17.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (115, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-7.0-10.0-12.0-17.0/bayesianoptimization/tuner0.json
+{'n_layers': 1, 'filter_unit0': 64, 'kernel_size0': 3, 'pool_size0': 2, 'stride_size0': 3, 'dropout0': 0.4}
+
 1/39 [..............................] - ETA: 5s
39/39 [==============================] - ETA: 0s
39/39 [==============================] - 0s 2ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+imu_rr_S01_id1_combi5.0-7.0-10.0-12.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (115, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-7.0-10.0-12.0-20.0/bayesianoptimization/tuner0.json
+{'n_layers': 1, 'filter_unit0': 32, 'kernel_size0': 4, 'pool_size0': 3, 'stride_size0': 1, 'dropout0': 0.4}
+
 1/39 [..............................] - ETA: 5s
39/39 [==============================] - ETA: 0s
39/39 [==============================] - 0s 2ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+imu_rr_S01_id1_combi5.0-7.0-10.0-15.0-17.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (115, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-7.0-10.0-15.0-17.0/bayesianoptimization/tuner0.json
+{'n_layers': 2, 'filter_unit0': 128, 'filter_unit1': 128, 'kernel_size0': 1, 'kernel_size1': 3, 'pool_size0': 5, 'pool_size1': 2, 'stride_size0': 4, 'stride_size1': 3, 'dropout0': 0.1, 'dropout1': 0.30000000000000004}
+
 1/39 [..............................] - ETA: 9s
24/39 [=================>............] - ETA: 0s
39/39 [==============================] - ETA: 0s
39/39 [==============================] - 0s 3ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+imu_rr_S01_id1_combi5.0-7.0-10.0-15.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (110, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-7.0-10.0-15.0-20.0/bayesianoptimization/tuner0.json
+{'n_layers': 1, 'filter_unit0': 64, 'kernel_size0': 2, 'pool_size0': 5, 'stride_size0': 3, 'dropout0': 0.1}
+
 1/39 [..............................] - ETA: 5s
39/39 [==============================] - ETA: 0s
39/39 [==============================] - 0s 2ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+imu_rr_S01_id1_combi5.0-7.0-10.0-17.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.13
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.13
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.14
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.14
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.15
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.15
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.16
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.16
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.17
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.17
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.18
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.18
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.19
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.19
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.20
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.20
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (115, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-7.0-10.0-17.0-20.0/bayesianoptimization/tuner0.json
+{'n_layers': 1, 'filter_unit0': 128, 'kernel_size0': 1, 'pool_size0': 3, 'stride_size0': 1, 'dropout0': 0.1}
+
 1/39 [..............................] - ETA: 5s
27/39 [===================>..........] - ETA: 0s
39/39 [==============================] - 0s 2ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+imu_rr_S01_id1_combi5.0-7.0-12.0-15.0-17.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (115, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-7.0-12.0-15.0-17.0/bayesianoptimization/tuner0.json
+{'n_layers': 4, 'filter_unit0': 256, 'filter_unit1': 64, 'filter_unit2': 64, 'filter_unit3': 256, 'kernel_size0': 3, 'kernel_size1': 4, 'kernel_size2': 5, 'kernel_size3': 5, 'pool_size0': 2, 'pool_size1': 5, 'pool_size2': 5, 'pool_size3': 3, 'stride_size0': 4, 'stride_size1': 5, 'stride_size2': 3, 'stride_size3': 2, 'dropout0': 0.2, 'dropout1': 0.4, 'dropout2': 0.1, 'dropout3': 0.4}
+
 1/39 [..............................] - ETA: 17s
16/39 [===========>..................] - ETA: 0s 
31/39 [======================>.......] - ETA: 0s
39/39 [==============================] - ETA: 0s
39/39 [==============================] - 1s 5ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+imu_rr_S01_id1_combi5.0-7.0-12.0-15.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (110, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-7.0-12.0-15.0-20.0/bayesianoptimization/tuner0.json
+{'n_layers': 1, 'filter_unit0': 64, 'kernel_size0': 4, 'pool_size0': 1, 'stride_size0': 2, 'dropout0': 0.30000000000000004}
+
 1/39 [..............................] - ETA: 5s
37/39 [===========================>..] - ETA: 0s
39/39 [==============================] - 0s 2ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+imu_rr_S01_id1_combi5.0-7.0-12.0-17.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (110, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-7.0-12.0-17.0-20.0/bayesianoptimization/tuner0.json
+{'n_layers': 1, 'filter_unit0': 32, 'kernel_size0': 5, 'pool_size0': 2, 'stride_size0': 1, 'dropout0': 0.30000000000000004}
+
 1/39 [..............................] - ETA: 7s
39/39 [==============================] - ETA: 0s
39/39 [==============================] - 0s 2ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.13
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.13
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.14
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.14
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.15
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.15
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.16
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.16
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.17
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.17
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.18
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.18
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.19
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.19
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.20
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.20
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.21
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.21
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.22
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.22
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.23
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.23
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.24
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.24
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.25
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.25
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.26
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.26
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.27
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.27
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.28
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.28
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.29
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.29
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.30
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.30
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.31
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.31
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.32
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.32
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.33
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.33
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.34
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.34
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.35
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.35
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.36
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.36
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+imu_rr_S01_id1_combi5.0-7.0-15.0-17.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (115, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-7.0-15.0-17.0-20.0/bayesianoptimization/tuner0.json
+{'n_layers': 3, 'filter_unit0': 32, 'filter_unit1': 64, 'filter_unit2': 64, 'kernel_size0': 2, 'kernel_size1': 3, 'kernel_size2': 3, 'pool_size0': 3, 'pool_size1': 2, 'pool_size2': 5, 'stride_size0': 5, 'stride_size1': 1, 'stride_size2': 3, 'dropout0': 0.1, 'dropout1': 0.0, 'dropout2': 0.2}
+
 1/39 [..............................] - ETA: 12s
34/39 [=========================>....] - ETA: 0s 
39/39 [==============================] - 0s 2ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+imu_rr_S01_id1_combi5.0-10.0-12.0-15.0-17.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (115, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-10.0-12.0-15.0-17.0/bayesianoptimization/tuner0.json
+{'n_layers': 1, 'filter_unit0': 128, 'kernel_size0': 4, 'pool_size0': 2, 'stride_size0': 5, 'dropout0': 0.30000000000000004}
+
 1/39 [..............................] - ETA: 4s
39/39 [==============================] - 0s 1ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+imu_rr_S01_id1_combi5.0-10.0-12.0-15.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (110, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-10.0-12.0-15.0-20.0/bayesianoptimization/tuner0.json
+{'n_layers': 4, 'filter_unit0': 32, 'filter_unit1': 256, 'filter_unit2': 256, 'filter_unit3': 256, 'kernel_size0': 5, 'kernel_size1': 1, 'kernel_size2': 5, 'kernel_size3': 2, 'pool_size0': 5, 'pool_size1': 1, 'pool_size2': 4, 'pool_size3': 2, 'stride_size0': 4, 'stride_size1': 5, 'stride_size2': 4, 'stride_size3': 4, 'dropout0': 0.1, 'dropout1': 0.2, 'dropout2': 0.1, 'dropout3': 0.0}
+
 1/39 [..............................] - ETA: 16s
26/39 [===================>..........] - ETA: 0s 
39/39 [==============================] - ETA: 0s
39/39 [==============================] - 1s 3ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.13
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.13
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.14
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.14
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.15
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.15
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.16
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.16
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.17
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.17
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.18
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.18
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.19
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.19
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.20
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.20
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.21
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.21
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.22
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.22
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.23
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.23
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.24
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.24
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.25
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.25
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.26
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.26
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.27
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.27
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.28
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.28
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+imu_rr_S01_id1_combi5.0-10.0-12.0-17.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (110, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-10.0-12.0-17.0-20.0/bayesianoptimization/tuner0.json
+{'n_layers': 5, 'filter_unit0': 128, 'filter_unit1': 64, 'filter_unit2': 256, 'filter_unit3': 256, 'filter_unit4': 256, 'kernel_size0': 3, 'kernel_size1': 1, 'kernel_size2': 1, 'kernel_size3': 4, 'kernel_size4': 2, 'pool_size0': 3, 'pool_size1': 2, 'pool_size2': 5, 'pool_size3': 4, 'pool_size4': 5, 'stride_size0': 3, 'stride_size1': 1, 'stride_size2': 2, 'stride_size3': 5, 'stride_size4': 2, 'dropout0': 0.0, 'dropout1': 0.4, 'dropout2': 0.30000000000000004, 'dropout3': 0.0, 'dropout4': 0.0}
+
 1/39 [..............................] - ETA: 21s
15/39 [==========>...................] - ETA: 0s 
28/39 [====================>.........] - ETA: 0s
39/39 [==============================] - ETA: 0s
39/39 [==============================] - 1s 6ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+imu_rr_S01_id1_combi5.0-10.0-15.0-17.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (110, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-10.0-15.0-17.0-20.0/bayesianoptimization/tuner0.json
+{'n_layers': 4, 'filter_unit0': 64, 'filter_unit1': 64, 'filter_unit2': 32, 'filter_unit3': 64, 'kernel_size0': 2, 'kernel_size1': 5, 'kernel_size2': 1, 'kernel_size3': 3, 'pool_size0': 5, 'pool_size1': 5, 'pool_size2': 5, 'pool_size3': 2, 'stride_size0': 2, 'stride_size1': 3, 'stride_size2': 2, 'stride_size3': 1, 'dropout0': 0.0, 'dropout1': 0.1, 'dropout2': 0.4, 'dropout3': 0.30000000000000004}
+
 1/39 [..............................] - ETA: 15s
33/39 [========================>.....] - ETA: 0s 
39/39 [==============================] - 1s 3ms/step
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+imu_rr_S01_id1_combi5.0-12.0-15.0-17.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+---CNN1D---
+input shape:  (1440, 6)
+x shape:  (115, 1440, 6)
+Reloading Tuner from /projects/CIBCIGroup/00DataUploading/rqchia/aria-respiration-cal/subject_specific/S01/imu_rr/01/cnn1d_imu_rr_S01_id1_combi5.0-12.0-15.0-17.0-20.0/bayesianoptimization/tuner0.json
+{'n_layers': 1, 'filter_unit0': 32, 'kernel_size0': 5, 'pool_size0': 4, 'stride_size0': 5, 'dropout0': 0.0}
+Traceback (most recent call last):
+  File "regress_rr.py", line 1521, in <module>
+    rr_func(subject)
+  File "regress_rr.py", line 1382, in sens_rr_model
+    preds = model.predict(x_test)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
+    raise e.with_traceback(filtered_tb) from None
+  File "/home/rqchia/.local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py", line 53, in quick_execute
+    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
+tensorflow.python.framework.errors_impl.InvalidArgumentError: Graph execution error:
+
+Detected at node 'cnn1d/dense_output/MatMul' defined at (most recent call last):
+    File "regress_rr.py", line 1521, in <module>
+      rr_func(subject)
+    File "regress_rr.py", line 1382, in sens_rr_model
+      preds = model.predict(x_test)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 65, in error_handler
+      return fn(*args, **kwargs)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 2554, in predict
+      tmp_batch_outputs = self.predict_function(iterator)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 2341, in predict_function
+      return step_function(self, iterator)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 2327, in step_function
+      outputs = model.distribute_strategy.run(run_step, args=(data,))
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 2315, in run_step
+      outputs = model.predict_step(data)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 2283, in predict_step
+      return self(x, training=False)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 65, in error_handler
+      return fn(*args, **kwargs)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/training.py", line 569, in __call__
+      return super().__call__(*args, **kwargs)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 65, in error_handler
+      return fn(*args, **kwargs)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/base_layer.py", line 1150, in __call__
+      outputs = call_fn(inputs, *args, **kwargs)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 96, in error_handler
+      return fn(*args, **kwargs)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/sequential.py", line 405, in call
+      return super().call(inputs, training=training, mask=mask)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/functional.py", line 512, in call
+      return self._run_internal_graph(inputs, training=training, mask=mask)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/functional.py", line 669, in _run_internal_graph
+      outputs = node.layer(*args, **kwargs)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 65, in error_handler
+      return fn(*args, **kwargs)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/engine/base_layer.py", line 1150, in __call__
+      outputs = call_fn(inputs, *args, **kwargs)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/utils/traceback_utils.py", line 96, in error_handler
+      return fn(*args, **kwargs)
+    File "/home/rqchia/.local/lib/python3.8/site-packages/keras/src/layers/core/dense.py", line 241, in call
+      outputs = tf.matmul(a=inputs, b=self.kernel)
+Node: 'cnn1d/dense_output/MatMul'
+Matrix size-incompatible: In[0]: [32,256], In[1]: [32,1]
+	 [[{{node cnn1d/dense_output/MatMul}}]] [Op:__inference_predict_function_11283]
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.13
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.13
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.14
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.14
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.15
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.15
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.16
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.16
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.17
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.17
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.18
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.18
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.19
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.19
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.20
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.20
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.21
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.21
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.22
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.22
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.23
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.23
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.24
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.24
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.25
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.25
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.26
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.26
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.27
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.27
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.28
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.28
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.29
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.29
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.30
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.30
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.31
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.31
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.32
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.32
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.33
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.33
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.34
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.34
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.35
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.35
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.36
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.36
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.13
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.13
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.14
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.14
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.15
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.15
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.16
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.16
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.17
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.17
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.18
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.18
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.19
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.19
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.20
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.20
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.21
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.21
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.22
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.22
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.23
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.23
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.24
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.24
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.25
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.25
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.26
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.26
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.27
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.27
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.28
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.28
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.29
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.29
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.30
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.30
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.31
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.31
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.32
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.32
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.33
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.33
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.34
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.34
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.35
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.35
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.36
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.36
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.37
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.37
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.38
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.38
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.39
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.39
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.40
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.40
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.41
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.41
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.42
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.42
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.43
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.43
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.44
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.44
+WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).layer_with_weights-4.kernel
+Value in checkpoint could not be found in the restored object: (root).layer_with_weights-4.kernel
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).layer_with_weights-4.bias
+Value in checkpoint could not be found in the restored object: (root).layer_with_weights-4.bias
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.1
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.2
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.3
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.4
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.5
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.6
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.7
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.8
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.9
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.10
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.11
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.12
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.13
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.13
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.14
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.14
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.15
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.15
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.16
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.16
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.17
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.17
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.18
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.18
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.19
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.19
+WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer._variables.20
+Value in checkpoint could not be found in the restored object: (root).optimizer._variables.20
diff --git a/logs/singularity_27064.out b/logs/singularity_27064.out
new file mode 100644
index 0000000000000000000000000000000000000000..eee0c3d76387c6afa7dd1f513432fbc2f2e8fdf8
--- /dev/null
+++ b/logs/singularity_27064.out
@@ -0,0 +1,33 @@
+2023-11-30 18:01:44.644763: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
+Traceback (most recent call last):
+  File "regress_rr.py", line 23, in <module>
+    import tensorflow as tf
+  File "/home/rqchia/.local/lib/python3.8/site-packages/tensorflow/__init__.py", line 52, in <module>
+    from ._api.v2 import compat
+  File "/home/rqchia/.local/lib/python3.8/site-packages/tensorflow/_api/v2/compat/__init__.py", line 37, in <module>
+    from . import v1
+  File "/home/rqchia/.local/lib/python3.8/site-packages/tensorflow/_api/v2/compat/v1/__init__.py", line 31, in <module>
+    from . import compat
+  File "/home/rqchia/.local/lib/python3.8/site-packages/tensorflow/_api/v2/compat/v1/compat/__init__.py", line 38, in <module>
+    from . import v2
+  File "/home/rqchia/.local/lib/python3.8/site-packages/tensorflow/_api/v2/compat/v1/compat/v2/__init__.py", line 28, in <module>
+    from tensorflow._api.v2.compat.v2 import __internal__
+  File "/home/rqchia/.local/lib/python3.8/site-packages/tensorflow/_api/v2/compat/v2/__init__.py", line 33, in <module>
+    from . import compat
+  File "/home/rqchia/.local/lib/python3.8/site-packages/tensorflow/_api/v2/compat/v2/compat/__init__.py", line 38, in <module>
+    from . import v2
+  File "/home/rqchia/.local/lib/python3.8/site-packages/tensorflow/_api/v2/compat/v2/compat/v2/__init__.py", line 34, in <module>
+    from tensorflow._api.v2.compat.v2 import config
+  File "/home/rqchia/.local/lib/python3.8/site-packages/tensorflow/_api/v2/compat/v2/config/__init__.py", line 9, in <module>
+    from . import optimizer
+  File "<frozen importlib._bootstrap>", line 991, in _find_and_load
+  File "<frozen importlib._bootstrap>", line 971, in _find_and_load_unlocked
+  File "<frozen importlib._bootstrap>", line 914, in _find_spec
+  File "<frozen importlib._bootstrap_external>", line 1407, in find_spec
+  File "<frozen importlib._bootstrap_external>", line 1379, in _get_spec
+  File "<frozen importlib._bootstrap_external>", line 1525, in find_spec
+  File "<frozen importlib._bootstrap_external>", line 156, in _path_isfile
+  File "<frozen importlib._bootstrap_external>", line 148, in _path_is_mode_type
+  File "<frozen importlib._bootstrap_external>", line 142, in _path_stat
+KeyboardInterrupt
diff --git a/logs/singularity_45963.out b/logs/singularity_45963.out
new file mode 100644
index 0000000000000000000000000000000000000000..acf4b71502aacd81ad29529b4a47d501b2ea0ded
--- /dev/null
+++ b/logs/singularity_45963.out
@@ -0,0 +1,45 @@
+2023-11-30 18:19:02.564572: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
+Using TensorFlow backend
+Namespace(data_input='imu', feature_method='minirocket', lbl_str='pss', method='ml', model='linreg', overwrite=0, subject=-1, test_standing=1, train_len=5, win_shift=0.2, win_size=12)
+Using pre-set data id:  0
+imu_rr_S02_id0_combi5.0-7.0-10.0-12.0-15.0
+train
+(36036, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+QStandardPaths: XDG_RUNTIME_DIR points to non-existing path '/run/user/56779', please create it with 0700 permissions.
+imu_rr_S02_id0_combi5.0-7.0-10.0-12.0-17.0
+train
+(35916, 10)
+test
+(287283, 9)
+minirocket transforming...
+Traceback (most recent call last):
+  File "regress_rr.py", line 1521, in <module>
+    rr_func(subject)
+  File "regress_rr.py", line 1347, in sens_rr_model
+    x_test     = minirocket.transform(x_test)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/sktime/transformations/base.py", line 533, in transform
+    Xt = self._transform(X=X_inner, y=y_inner)
+  File "/home/rqchia/.local/lib/python3.8/site-packages/sktime/transformations/panel/rocket/_minirocket_multivariate.py", line 152, in _transform
+    X_ = _transform_multi(X, self.parameters)
+  File "/usr/local/lib/python3.8/dist-packages/numba/core/serialize.py", line 30, in _numba_unpickle
+    def _numba_unpickle(address, bytedata, hashed):
+KeyboardInterrupt
diff --git a/logs/singularity_50102.out b/logs/singularity_50102.out
new file mode 100644
index 0000000000000000000000000000000000000000..419bb2cd392e3f48c4ffe366e296b329d32f3ebf
--- /dev/null
+++ b/logs/singularity_50102.out
@@ -0,0 +1,2724 @@
+2023-11-30 18:22:21.025164: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
+To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
+Using TensorFlow backend
+Namespace(data_input='imu', feature_method='minirocket', lbl_str='pss', method='ml', model='linreg', overwrite=0, subject=-1, test_standing=1, train_len=5, win_shift=0.2, win_size=12)
+Using pre-set data id:  0
+imu_rr_S01_id0_combi5.0-7.0-10.0-12.0-15.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+QStandardPaths: XDG_RUNTIME_DIR points to non-existing path '/run/user/56779', please create it with 0700 permissions.
+imu_rr_S01_id0_combi5.0-7.0-10.0-12.0-17.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-7.0-10.0-12.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-7.0-10.0-15.0-17.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-7.0-10.0-15.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-7.0-10.0-17.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-7.0-12.0-15.0-17.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-7.0-12.0-15.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-7.0-12.0-17.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-7.0-15.0-17.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-10.0-12.0-15.0-17.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-10.0-12.0-15.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-10.0-12.0-17.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-10.0-15.0-17.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi5.0-12.0-15.0-17.0-20.0
+train
+(35921, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi7.0-10.0-12.0-15.0-17.0
+train
+(35920, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi7.0-10.0-12.0-15.0-20.0
+train
+(35920, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi7.0-10.0-12.0-17.0-20.0
+train
+(35920, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi7.0-10.0-15.0-17.0-20.0
+train
+(35920, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
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+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(35920, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S01_id0_combi10.0-12.0-15.0-17.0-20.0
+train
+(35920, 10)
+test
+(364536, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+Using pre-set data id:  0
+imu_rr_S02_id0_combi5.0-7.0-10.0-12.0-15.0
+train
+(36036, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
+imu_rr_S02_id0_combi5.0-7.0-10.0-12.0-17.0
+train
+(35916, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
+imu_rr_S02_id0_combi5.0-7.0-10.0-12.0-20.0
+train
+(36036, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(36036, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(36156, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(36036, 10)
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+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(36036, 10)
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+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(36156, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(36036, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(36156, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(36036, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(36156, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(36036, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(36156, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(36156, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
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+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S02_id0_combi7.0-10.0-12.0-15.0-17.0
+train
+(36035, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
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+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S02_id0_combi7.0-10.0-12.0-15.0-20.0
+train
+(36155, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S02_id0_combi7.0-10.0-12.0-17.0-20.0
+train
+(36035, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S02_id0_combi7.0-10.0-15.0-17.0-20.0
+train
+(36155, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S02_id0_combi7.0-12.0-15.0-17.0-20.0
+train
+(36155, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
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+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S02_id0_combi10.0-12.0-15.0-17.0-20.0
+train
+(36155, 10)
+test
+(287283, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
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+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+Using pre-set data id:  0
+imu_rr_S03_id0_combi5.0-7.0-10.0-12.0-15.0
+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
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+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S03_id0_combi5.0-7.0-10.0-12.0-17.0
+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
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+
+[653 rows x 18 columns]
+imu_rr_S03_id0_combi5.0-7.0-10.0-12.0-20.0
+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
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+
+[653 rows x 18 columns]
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+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
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+
+[653 rows x 18 columns]
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+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
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+
+[653 rows x 18 columns]
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+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+
+[653 rows x 18 columns]
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+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
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+
+[653 rows x 18 columns]
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+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
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+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S03_id0_combi5.0-10.0-12.0-17.0-20.0
+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S03_id0_combi5.0-10.0-15.0-17.0-20.0
+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S03_id0_combi5.0-12.0-15.0-17.0-20.0
+train
+(35921, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S03_id0_combi7.0-10.0-12.0-15.0-17.0
+train
+(35920, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S03_id0_combi7.0-10.0-12.0-15.0-20.0
+train
+(35920, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S03_id0_combi7.0-10.0-12.0-17.0-20.0
+train
+(35920, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S03_id0_combi7.0-10.0-15.0-17.0-20.0
+train
+(35920, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S03_id0_combi7.0-12.0-15.0-17.0-20.0
+train
+(35920, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+imu_rr_S03_id0_combi10.0-12.0-15.0-17.0-20.0
+train
+(35920, 10)
+test
+(287299, 9)
+minirocket transforming...
+---LinearRegression---
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+648     S01          0     ard  ...  -1.383741       -0.000775      0.978195
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+
+[653 rows x 18 columns]
+unable to find matching config id
+Data id not set, auto assigned to:  0
+imu_rr_S04_id0_combi5.0-7.0-10.0-12.0-15.0
+train
+(35921, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+649     S01          0     ard  ...  -1.373163       -0.018246      0.519927
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+653     S04          0  linreg  ...  -4.992226        0.020375      0.523425
+
+[654 rows x 18 columns]
+imu_rr_S04_id0_combi5.0-7.0-10.0-12.0-17.0
+train
+(35921, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+650     S01          0     ard  ...  -0.843614       -0.027689      0.328764
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+653     S04          0  linreg  ...  -4.992226        0.020375      0.523425
+654     S04          0  linreg  ...  -4.486957       -0.067075      0.035493
+
+[655 rows x 18 columns]
+imu_rr_S04_id0_combi5.0-7.0-10.0-12.0-20.0
+train
+(35920, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+651     S01          0     ard  ...  -0.483776        0.012526      0.658679
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+653     S04          0  linreg  ...  -4.992226        0.020375      0.523425
+654     S04          0  linreg  ...  -4.486957       -0.067075      0.035493
+655     S04          0  linreg  ...  -8.317642       -0.033834      0.289262
+
+[656 rows x 18 columns]
+imu_rr_S04_id0_combi5.0-7.0-10.0-15.0-17.0
+train
+(35921, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+652     S01          0     ard  ...  -0.740169       -0.081858      0.003835
+653     S04          0  linreg  ...  -4.992226        0.020375      0.523425
+654     S04          0  linreg  ...  -4.486957       -0.067075      0.035493
+655     S04          0  linreg  ...  -8.317642       -0.033834      0.289262
+656     S04          0  linreg  ...  -3.635692       -0.014839      0.642159
+
+[657 rows x 18 columns]
+imu_rr_S04_id0_combi5.0-7.0-10.0-15.0-20.0
+train
+(35920, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+653     S04          0  linreg  ...  -4.992226        0.020375      0.523425
+654     S04          0  linreg  ...  -4.486957       -0.067075      0.035493
+655     S04          0  linreg  ...  -8.317642       -0.033834      0.289262
+656     S04          0  linreg  ...  -3.635692       -0.014839      0.642159
+657     S04          0  linreg  ...  -8.856661       -0.013460      0.673397
+
+[658 rows x 18 columns]
+imu_rr_S04_id0_combi5.0-7.0-10.0-17.0-20.0
+train
+(35920, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+655     S04          0  linreg  ...  -8.317642       -0.033834      0.289262
+656     S04          0  linreg  ...  -3.635692       -0.014839      0.642159
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+658     S04          0  linreg  ...  -6.366705       -0.019279      0.546018
+
+[659 rows x 18 columns]
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+(35921, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+655     S04          0  linreg  ...  -8.317642       -0.033834      0.289262
+656     S04          0  linreg  ...  -3.635692       -0.014839      0.642159
+657     S04          0  linreg  ...  -8.856661       -0.013460      0.673397
+658     S04          0  linreg  ...  -6.366705       -0.019279      0.546018
+659     S04          0  linreg  ...  -5.464115        0.013095      0.681751
+
+[660 rows x 18 columns]
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+train
+(35920, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+656     S04          0  linreg  ...  -3.635692       -0.014839      0.642159
+657     S04          0  linreg  ...  -8.856661       -0.013460      0.673397
+658     S04          0  linreg  ...  -6.366705       -0.019279      0.546018
+659     S04          0  linreg  ...  -5.464115        0.013095      0.681751
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+
+[661 rows x 18 columns]
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+train
+(35920, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
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+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
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+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+663     S04          0  linreg  ...  -5.690539        0.026037      0.414816
+664     S04          0  linreg  ...  -9.717190        0.014684      0.645642
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+(35920, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+662     S04          0  linreg  ...  -6.228437       -0.053016      0.096665
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+664     S04          0  linreg  ...  -9.717190        0.014684      0.645642
+665     S04          0  linreg  ...  -8.995283        0.001889      0.952839
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+train
+(35920, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+663     S04          0  linreg  ...  -5.690539        0.026037      0.414816
+664     S04          0  linreg  ...  -9.717190        0.014684      0.645642
+665     S04          0  linreg  ...  -8.995283        0.001889      0.952839
+666     S04          0  linreg  ...  -7.429890        0.045048      0.158155
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+(35920, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+664     S04          0  linreg  ...  -9.717190        0.014684      0.645642
+665     S04          0  linreg  ...  -8.995283        0.001889      0.952839
+666     S04          0  linreg  ...  -7.429890        0.045048      0.158155
+667     S04          0  linreg  ...  -8.187567        0.046483      0.145306
+
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+train
+(35920, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+665     S04          0  linreg  ...  -8.995283        0.001889      0.952839
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+667     S04          0  linreg  ...  -8.187567        0.046483      0.145306
+668     S04          0  linreg  ...  -2.763158        0.002265      0.943462
+
+[669 rows x 18 columns]
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+train
+(35919, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+666     S04          0  linreg  ...  -7.429890        0.045048      0.158155
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+669     S04          0  linreg  ...  -5.514833        0.018421      0.564022
+
+[670 rows x 18 columns]
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+train
+(35919, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+667     S04          0  linreg  ...  -8.187567        0.046483      0.145306
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+669     S04          0  linreg  ...  -5.514833        0.018421      0.564022
+670     S04          0  linreg  ...  -4.653449       -0.004663      0.883909
+
+[671 rows x 18 columns]
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+train
+(35919, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+668     S04          0  linreg  ...  -2.763158        0.002265      0.943462
+669     S04          0  linreg  ...  -5.514833        0.018421      0.564022
+670     S04          0  linreg  ...  -4.653449       -0.004663      0.883909
+671     S04          0  linreg  ...  -3.206832        0.039558      0.215283
+
+[672 rows x 18 columns]
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+train
+(35919, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+669     S04          0  linreg  ...  -5.514833        0.018421      0.564022
+670     S04          0  linreg  ...  -4.653449       -0.004663      0.883909
+671     S04          0  linreg  ...  -3.206832        0.039558      0.215283
+672     S04          0  linreg  ...  -4.749055        0.068482      0.031803
+
+[673 rows x 18 columns]
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+train
+(35919, 10)
+test
+(287280, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+670     S04          0  linreg  ...  -4.653449       -0.004663      0.883909
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+672     S04          0  linreg  ...  -4.749055        0.068482      0.031803
+673     S04          0  linreg  ...  -2.990206        0.137916      0.000014
+
+[674 rows x 18 columns]
+unable to find matching config id
+Data id not set, auto assigned to:  0
+imu_rr_S05_id0_combi5.0-7.0-10.0-12.0-15.0
+train
+(35920, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+673     S04          0  linreg  ...  -2.990206        0.137916      0.000014
+674     S05          0  linreg  ...  -2.415757        0.039849      0.213093
+
+[675 rows x 18 columns]
+imu_rr_S05_id0_combi5.0-7.0-10.0-12.0-17.0
+train
+(35920, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+671     S04          0  linreg  ...  -3.206832        0.039558      0.215283
+672     S04          0  linreg  ...  -4.749055        0.068482      0.031803
+673     S04          0  linreg  ...  -2.990206        0.137916      0.000014
+674     S05          0  linreg  ...  -2.415757        0.039849      0.213093
+675     S05          0  linreg  ...  -2.600227        0.015332      0.632023
+
+[676 rows x 18 columns]
+imu_rr_S05_id0_combi5.0-7.0-10.0-12.0-20.0
+train
+(35921, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+672     S04          0  linreg  ...  -4.749055        0.068482      0.031803
+673     S04          0  linreg  ...  -2.990206        0.137916      0.000014
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+676     S05          0  linreg  ...  -4.361863        0.078120      0.014539
+
+[677 rows x 18 columns]
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+train
+(35919, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+673     S04          0  linreg  ...  -2.990206        0.137916      0.000014
+674     S05          0  linreg  ...  -2.415757        0.039849      0.213093
+675     S05          0  linreg  ...  -2.600227        0.015332      0.632023
+676     S05          0  linreg  ...  -4.361863        0.078120      0.014539
+677     S05          0  linreg  ...  -2.362516        0.016706      0.601796
+
+[678 rows x 18 columns]
+imu_rr_S05_id0_combi5.0-7.0-10.0-15.0-20.0
+train
+(35920, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+674     S05          0  linreg  ...  -2.415757        0.039849      0.213093
+675     S05          0  linreg  ...  -2.600227        0.015332      0.632023
+676     S05          0  linreg  ...  -4.361863        0.078120      0.014539
+677     S05          0  linreg  ...  -2.362516        0.016706      0.601796
+678     S05          0  linreg  ...  -4.782338        0.058462      0.067625
+
+[679 rows x 18 columns]
+imu_rr_S05_id0_combi5.0-7.0-10.0-17.0-20.0
+train
+(35920, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+minirocket transforming...
+---LinearRegression---
+adding new entry
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+---LinearRegression---
+adding new entry
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+---LinearRegression---
+adding new entry
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+---LinearRegression---
+adding new entry
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+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+682     S05          0  linreg  ...  -2.502070        0.014022      0.661411
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+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
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+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
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+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
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+683     S05          0  linreg  ...  -2.785896        0.018241      0.568844
+684     S05          0  linreg  ...  -1.760125        0.035057      0.273396
+685     S05          0  linreg  ...  -2.716079        0.083430      0.009046
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+train
+(35919, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+682     S05          0  linreg  ...  -2.502070        0.014022      0.661411
+683     S05          0  linreg  ...  -2.785896        0.018241      0.568844
+684     S05          0  linreg  ...  -1.760125        0.035057      0.273396
+685     S05          0  linreg  ...  -2.716079        0.083430      0.009046
+686     S05          0  linreg  ...  -2.189085        0.044920      0.160414
+
+[687 rows x 18 columns]
+imu_rr_S05_id0_combi5.0-10.0-15.0-17.0-20.0
+train
+(35918, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+683     S05          0  linreg  ...  -2.785896        0.018241      0.568844
+684     S05          0  linreg  ...  -1.760125        0.035057      0.273396
+685     S05          0  linreg  ...  -2.716079        0.083430      0.009046
+686     S05          0  linreg  ...  -2.189085        0.044920      0.160414
+687     S05          0  linreg  ...  -2.174184        0.011584      0.717482
+
+[688 rows x 18 columns]
+imu_rr_S05_id0_combi5.0-12.0-15.0-17.0-20.0
+train
+(35918, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+684     S05          0  linreg  ...  -1.760125        0.035057      0.273396
+685     S05          0  linreg  ...  -2.716079        0.083430      0.009046
+686     S05          0  linreg  ...  -2.189085        0.044920      0.160414
+687     S05          0  linreg  ...  -2.174184        0.011584      0.717482
+688     S05          0  linreg  ...  -2.081208        0.016677      0.602433
+
+[689 rows x 18 columns]
+imu_rr_S05_id0_combi7.0-10.0-12.0-15.0-17.0
+train
+(35919, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+685     S05          0  linreg  ...  -2.716079        0.083430      0.009046
+686     S05          0  linreg  ...  -2.189085        0.044920      0.160414
+687     S05          0  linreg  ...  -2.174184        0.011584      0.717482
+688     S05          0  linreg  ...  -2.081208        0.016677      0.602433
+689     S05          0  linreg  ...  -1.511092       -0.025032      0.434240
+
+[690 rows x 18 columns]
+imu_rr_S05_id0_combi7.0-10.0-12.0-15.0-20.0
+train
+(35920, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+686     S05          0  linreg  ...  -2.189085        0.044920      0.160414
+687     S05          0  linreg  ...  -2.174184        0.011584      0.717482
+688     S05          0  linreg  ...  -2.081208        0.016677      0.602433
+689     S05          0  linreg  ...  -1.511092       -0.025032      0.434240
+690     S05          0  linreg  ...  -2.070153        0.040631      0.204247
+
+[691 rows x 18 columns]
+imu_rr_S05_id0_combi7.0-10.0-12.0-17.0-20.0
+train
+(35920, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+687     S05          0  linreg  ...  -2.174184        0.011584      0.717482
+688     S05          0  linreg  ...  -2.081208        0.016677      0.602433
+689     S05          0  linreg  ...  -1.511092       -0.025032      0.434240
+690     S05          0  linreg  ...  -2.070153        0.040631      0.204247
+691     S05          0  linreg  ...  -1.875947       -0.004190      0.895874
+
+[692 rows x 18 columns]
+imu_rr_S05_id0_combi7.0-10.0-15.0-17.0-20.0
+train
+(35919, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+688     S05          0  linreg  ...  -2.081208        0.016677      0.602433
+689     S05          0  linreg  ...  -1.511092       -0.025032      0.434240
+690     S05          0  linreg  ...  -2.070153        0.040631      0.204247
+691     S05          0  linreg  ...  -1.875947       -0.004190      0.895874
+692     S05          0  linreg  ...  -2.352758       -0.027399      0.392041
+
+[693 rows x 18 columns]
+imu_rr_S05_id0_combi7.0-12.0-15.0-17.0-20.0
+train
+(35919, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+689     S05          0  linreg  ...  -1.511092       -0.025032      0.434240
+690     S05          0  linreg  ...  -2.070153        0.040631      0.204247
+691     S05          0  linreg  ...  -1.875947       -0.004190      0.895874
+692     S05          0  linreg  ...  -2.352758       -0.027399      0.392041
+693     S05          0  linreg  ...  -1.805310       -0.016619      0.603699
+
+[694 rows x 18 columns]
+imu_rr_S05_id0_combi10.0-12.0-15.0-17.0-20.0
+train
+(35918, 10)
+test
+(287296, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776      0.364940
+1       S01          0  linreg  ... -11.875765        0.070097      0.101171
+2       S01          0  linreg  ... -11.069278        0.047023      0.271822
+3       S01          0  linreg  ... -25.345517        0.016892      0.693177
+4       S01          0  linreg  ... -15.299470        0.118749      0.005380
+..      ...        ...     ...  ...        ...             ...           ...
+690     S05          0  linreg  ...  -2.070153        0.040631      0.204247
+691     S05          0  linreg  ...  -1.875947       -0.004190      0.895874
+692     S05          0  linreg  ...  -2.352758       -0.027399      0.392041
+693     S05          0  linreg  ...  -1.805310       -0.016619      0.603699
+694     S05          0  linreg  ...  -0.661158       -0.003639      0.909507
+
+[695 rows x 18 columns]
+unable to find matching config id
+Data id not set, auto assigned to:  0
+imu_rr_S06_id0_combi5.0-7.0-10.0-12.0-15.0
+train
+(35923, 10)
+test
+(287294, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+691     S05          0  linreg  ...  -1.875947       -0.004190  8.958740e-01
+692     S05          0  linreg  ...  -2.352758       -0.027399  3.920409e-01
+693     S05          0  linreg  ...  -1.805310       -0.016619  6.036987e-01
+694     S05          0  linreg  ...  -0.661158       -0.003639  9.095073e-01
+695     S06          0  linreg  ...  -2.247136       -0.192894  1.077985e-09
+
+[696 rows x 18 columns]
+imu_rr_S06_id0_combi5.0-7.0-10.0-12.0-17.0
+train
+(35923, 10)
+test
+(287294, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+692     S05          0  linreg  ...  -2.352758       -0.027399  3.920409e-01
+693     S05          0  linreg  ...  -1.805310       -0.016619  6.036987e-01
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+---LinearRegression---
+adding new entry
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+adding new entry
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+adding new entry
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+---LinearRegression---
+adding new entry
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+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+709     S06          0  linreg  ...  -2.120085       -0.145204  4.853763e-06
+710     S06          0  linreg  ...  -1.588710       -0.162305  3.117620e-07
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+
+[714 rows x 18 columns]
+imu_rr_S06_id0_combi7.0-12.0-15.0-17.0-20.0
+train
+(35921, 10)
+test
+(287294, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+710     S06          0  linreg  ...  -1.588710       -0.162305  3.117620e-07
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+
+[715 rows x 18 columns]
+imu_rr_S06_id0_combi10.0-12.0-15.0-17.0-20.0
+train
+(35920, 10)
+test
+(287294, 9)
+minirocket transforming...
+---LinearRegression---
+adding new entry
+    subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
+0       S01          0  linreg  ...  -9.864563        0.038776  3.649402e-01
+1       S01          0  linreg  ... -11.875765        0.070097  1.011711e-01
+2       S01          0  linreg  ... -11.069278        0.047023  2.718220e-01
+3       S01          0  linreg  ... -25.345517        0.016892  6.931765e-01
+4       S01          0  linreg  ... -15.299470        0.118749  5.380273e-03
+..      ...        ...     ...  ...        ...             ...           ...
+711     S06          0  linreg  ...  -2.382225       -0.203053  1.316660e-10
+712     S06          0  linreg  ...  -2.299251       -0.189599  2.081305e-09
+713     S06          0  linreg  ...  -2.151206       -0.211608  2.054503e-11
+714     S06          0  linreg  ...  -2.041921       -0.177991  1.928055e-08
+715     S06          0  linreg  ...  -0.976966       -0.195415  6.463433e-10
+
+[716 rows x 18 columns]
+Namespace(data_input='imu', feature_method='minirocket', lbl_str='pss', method='ml', model='linreg', overwrite=0, subject=-1, test_standing=1, train_len=5, win_shift=0.2, win_size=12)
diff --git a/regress_rr.py b/regress_rr.py
index 112f84c2d4d26f83ffb6f3f67735825deb3d93df..506396864b80d539537d0d7945c655f788aa6cfe 100644
--- a/regress_rr.py
+++ b/regress_rr.py
@@ -70,6 +70,7 @@ from sktime.transformations.panel.rocket import (
 from config import WINDOW_SIZE, WINDOW_SHIFT, IMU_FS, DATA_DIR, BR_FS\
         , FS_RESAMPLE, PPG_FS
 
+N_SUBJECT_MAX = 6
 IMU_COLS =  ['acc_x', 'acc_y', 'acc_z', 'gyro_x', 'gyro_y', 'gyro_z']
 
 def utc_to_local(utc_dt, tz=None):
@@ -1422,8 +1423,8 @@ def arg_parser():
                                  'elastic'],
                        )
     parser.add_argument("-s", '--subject', type=int,
-                        default=2,
-                        choices=list(range(1,5))+[-1],
+                        default=1,
+                        choices=list(range(1,N_SUBJECT_MAX))+[-1],
                        )
     parser.add_argument("-f", '--feature_method', type=str,
                         default='minirocket',
@@ -1466,7 +1467,6 @@ def arg_parser():
 
 if __name__ == '__main__':
     np.random.seed(100)
-    n_subject_max = 4
     args = arg_parser()
 
     # Load command line arguments
@@ -1485,7 +1485,7 @@ if __name__ == '__main__':
     print(args)
     assert train_len>0,"--train_len must be an integer greater than 0"
 
-    subject_pre_string = 'Pilot'
+    subject_pre_string = 'S' # Pilot / S
 
     if subject > 0 and method == 'ml':
         subject = subject_pre_string+str(subject).zfill(2)
@@ -1503,7 +1503,7 @@ if __name__ == '__main__':
                      )
     elif subject <= 0 and method == 'ml':
         subjects = [subject_pre_string+str(i).zfill(2) for i in \
-                    range(2, n_subject_max+1)]
+                    range(1, N_SUBJECT_MAX+1)]
 
         rr_func = partial(sens_rr_model,
                           window_size=window_size,
@@ -1530,7 +1530,7 @@ if __name__ == '__main__':
                    test_standing=test_standing)
     elif subject <= 0 and method == 'ml':
         subjects = [subject_pre_string+str(i).zfill(2) for i in \
-                    range(2, n_subject_max+1)]
+                    range(1, n_subject_max+1)]
 
         rr_func = partial(sens_rr_model,
                           window_size=window_size,