2023-11-26 01:21:46.434356: 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-bvp', feature_method='tsfresh', lbl_str='pss', model='linreg', overwrite=1, subject=3, test_standing=1, train_len=5, win_shift=0.2, win_size=12)
Using pre-set data id:  2
Dependency not available for matrix_profile, this feature will be disabled!

Feature Extraction:   0%|          | 0/65 [00:00<?, ?it/s]
Feature Extraction:   2%|▏         | 1/65 [05:32<5:54:39, 332.48s/it]
Feature Extraction:   3%|▎         | 2/65 [05:34<2:25:10, 138.27s/it]
Feature Extraction:   5%|▍         | 3/65 [05:36<1:18:40, 76.14s/it] 
Feature Extraction:   6%|▌         | 4/65 [05:38<47:35, 46.82s/it]  
Feature Extraction:   8%|▊         | 5/65 [05:40<30:41, 30.69s/it]
Feature Extraction:   9%|▉         | 6/65 [05:42<20:18, 20.65s/it]
Feature Extraction:  11%|█         | 7/65 [05:43<13:49, 14.30s/it]
Feature Extraction:  12%|█▏        | 8/65 [05:44<09:34, 10.08s/it]
Feature Extraction:  14%|█▍        | 9/65 [05:48<07:31,  8.07s/it]
Feature Extraction:  15%|█▌        | 10/65 [05:48<05:15,  5.73s/it]
Feature Extraction:  17%|█▋        | 11/65 [05:49<03:49,  4.24s/it]
Feature Extraction:  18%|█▊        | 12/65 [05:50<02:47,  3.17s/it]
Feature Extraction:  20%|██        | 13/65 [05:51<02:12,  2.55s/it]
Feature Extraction:  22%|██▏       | 14/65 [11:02<1:21:18, 95.65s/it]
Feature Extraction:  23%|██▎       | 15/65 [11:09<57:27, 68.94s/it]  
Feature Extraction:  25%|██▍       | 16/65 [11:12<40:05, 49.08s/it]
Feature Extraction:  26%|██▌       | 17/65 [11:13<27:49, 34.78s/it]
Feature Extraction:  28%|██▊       | 18/65 [11:13<19:05, 24.36s/it]
Feature Extraction:  29%|██▉       | 19/65 [11:14<13:10, 17.18s/it]
Feature Extraction:  31%|███       | 20/65 [11:19<10:16, 13.70s/it]
Feature Extraction:  32%|███▏      | 21/65 [11:19<07:05,  9.68s/it]
Feature Extraction:  34%|███▍      | 22/65 [11:21<05:09,  7.19s/it]
Feature Extraction:  35%|███▌      | 23/65 [11:21<03:35,  5.14s/it]
Feature Extraction:  37%|███▋      | 24/65 [11:22<02:36,  3.81s/it]
Feature Extraction:  38%|███▊      | 25/65 [11:25<02:18,  3.46s/it]
Feature Extraction:  40%|████      | 26/65 [11:27<02:08,  3.29s/it]
Feature Extraction:  42%|████▏     | 27/65 [16:36<1:00:02, 94.79s/it]
Feature Extraction:  43%|████▎     | 28/65 [16:38<41:21, 67.06s/it]  
Feature Extraction:  45%|████▍     | 29/65 [16:39<28:21, 47.25s/it]
Feature Extraction:  46%|████▌     | 30/65 [16:41<19:31, 33.48s/it]
Feature Extraction:  48%|████▊     | 31/65 [16:48<14:28, 25.54s/it]
Feature Extraction:  49%|████▉     | 32/65 [16:48<09:51, 17.92s/it]
Feature Extraction:  51%|█████     | 33/65 [16:48<06:42, 12.58s/it]
Feature Extraction:  52%|█████▏    | 34/65 [16:50<04:50,  9.37s/it]
Feature Extraction:  54%|█████▍    | 35/65 [16:53<03:44,  7.49s/it]
Feature Extraction:  55%|█████▌    | 36/65 [16:56<02:58,  6.14s/it]
Feature Extraction:  57%|█████▋    | 37/65 [16:57<02:13,  4.75s/it]
Feature Extraction:  58%|█████▊    | 38/65 [16:59<01:40,  3.73s/it]
Feature Extraction:  60%|██████    | 39/65 [17:01<01:25,  3.30s/it]
Feature Extraction:  62%|██████▏   | 40/65 [22:06<39:02, 93.69s/it]
Feature Extraction:  63%|██████▎   | 41/65 [22:10<26:42, 66.78s/it]
Feature Extraction:  65%|██████▍   | 42/65 [22:10<17:56, 46.80s/it]
Feature Extraction:  66%|██████▌   | 43/65 [22:11<12:07, 33.05s/it]
Feature Extraction:  68%|██████▊   | 44/65 [22:16<08:39, 24.73s/it]
Feature Extraction:  69%|██████▉   | 45/65 [22:18<06:00, 18.01s/it]
Feature Extraction:  71%|███████   | 46/65 [22:19<04:03, 12.83s/it]
Feature Extraction:  72%|███████▏  | 47/65 [22:21<02:50,  9.44s/it]
Feature Extraction:  74%|███████▍  | 48/65 [22:24<02:07,  7.50s/it]
Feature Extraction:  75%|███████▌  | 49/65 [22:24<01:25,  5.33s/it]
Feature Extraction:  77%|███████▋  | 50/65 [22:28<01:12,  4.86s/it]
Feature Extraction:  78%|███████▊  | 51/65 [22:28<00:48,  3.49s/it]
Feature Extraction:  80%|████████  | 52/65 [22:29<00:34,  2.69s/it]
Feature Extraction:  82%|████████▏ | 53/65 [25:40<11:52, 59.34s/it]
Feature Extraction:  83%|████████▎ | 54/65 [27:29<13:36, 74.23s/it]
Feature Extraction:  85%|████████▍ | 55/65 [27:30<08:42, 52.22s/it]
Feature Extraction:  86%|████████▌ | 56/65 [27:31<05:30, 36.70s/it]
Feature Extraction:  88%|████████▊ | 57/65 [27:36<03:38, 27.26s/it]
Feature Extraction:  89%|████████▉ | 58/65 [27:39<02:19, 19.91s/it]
Feature Extraction:  91%|█████████ | 59/65 [27:41<01:27, 14.56s/it]
Feature Extraction:  92%|█████████▏| 60/65 [27:42<00:53, 10.72s/it]
Feature Extraction:  94%|█████████▍| 61/65 [27:43<00:31,  7.80s/it]
Feature Extraction:  95%|█████████▌| 62/65 [27:44<00:16,  5.63s/it]
Feature Extraction:  97%|█████████▋| 63/65 [27:47<00:09,  4.86s/it]
Feature Extraction:  98%|█████████▊| 64/65 [27:49<00:04,  4.10s/it]
Feature Extraction: 100%|██████████| 65/65 [27:50<00:00,  3.17s/it]
Feature Extraction: 100%|██████████| 65/65 [27:50<00:00, 25.70s/it]
Dependency not available for matrix_profile, this feature will be disabled!

Feature Extraction:   0%|          | 0/47 [00:00<?, ?it/s]
Feature Extraction:   2%|▏         | 1/47 [00:08<06:53,  9.00s/it]
Feature Extraction:   4%|▍         | 2/47 [00:09<02:50,  3.79s/it]
Feature Extraction:   9%|▊         | 4/47 [00:09<01:04,  1.50s/it]
Feature Extraction:  15%|█▍        | 7/47 [00:09<00:28,  1.38it/s]
Feature Extraction:  17%|█▋        | 8/47 [00:09<00:23,  1.68it/s]
Feature Extraction:  19%|█▉        | 9/47 [00:10<00:19,  1.99it/s]
Feature Extraction:  26%|██▌       | 12/47 [00:10<00:09,  3.55it/s]
Feature Extraction:  28%|██▊       | 13/47 [00:10<00:11,  3.08it/s]
Feature Extraction:  30%|██▉       | 14/47 [00:19<01:07,  2.03s/it]
Feature Extraction:  32%|███▏      | 15/47 [00:19<00:50,  1.59s/it]
Feature Extraction:  36%|███▌      | 17/47 [00:19<00:29,  1.01it/s]
Feature Extraction:  40%|████      | 19/47 [00:19<00:20,  1.38it/s]
Feature Extraction:  43%|████▎     | 20/47 [00:20<00:17,  1.58it/s]
Feature Extraction:  47%|████▋     | 22/47 [00:20<00:10,  2.32it/s]
Feature Extraction:  51%|█████     | 24/47 [00:20<00:08,  2.65it/s]
Feature Extraction:  55%|█████▌    | 26/47 [00:21<00:07,  2.78it/s]
Feature Extraction:  57%|█████▋    | 27/47 [00:28<00:31,  1.55s/it]
Feature Extraction:  60%|█████▉    | 28/47 [00:28<00:25,  1.34s/it]
Feature Extraction:  62%|██████▏   | 29/47 [00:28<00:19,  1.06s/it]
Feature Extraction:  64%|██████▍   | 30/47 [00:29<00:14,  1.20it/s]
Feature Extraction:  66%|██████▌   | 31/47 [00:29<00:11,  1.44it/s]
Feature Extraction:  70%|███████   | 33/47 [00:29<00:05,  2.34it/s]
Feature Extraction:  72%|███████▏  | 34/47 [00:29<00:04,  2.80it/s]
Feature Extraction:  74%|███████▍  | 35/47 [00:30<00:05,  2.39it/s]
Feature Extraction:  77%|███████▋  | 36/47 [00:30<00:04,  2.35it/s]
Feature Extraction:  83%|████████▎ | 39/47 [00:31<00:02,  3.04it/s]
Feature Extraction:  85%|████████▌ | 40/47 [00:34<00:06,  1.03it/s]
Feature Extraction:  87%|████████▋ | 41/47 [00:35<00:05,  1.13it/s]
Feature Extraction:  89%|████████▉ | 42/47 [00:36<00:04,  1.09it/s]
Feature Extraction:  94%|█████████▎| 44/47 [00:37<00:01,  1.58it/s]
Feature Extraction:  96%|█████████▌| 45/47 [00:37<00:01,  1.86it/s]
Feature Extraction:  98%|█████████▊| 46/47 [00:37<00:00,  2.22it/s]
Feature Extraction: 100%|██████████| 47/47 [00:37<00:00,  1.26it/s]
Dependency not available for matrix_profile, this feature will be disabled!

Feature Extraction:   0%|          | 0/47 [00:00<?, ?it/s]
Feature Extraction:   2%|▏         | 1/47 [00:08<06:43,  8.78s/it]
Feature Extraction:   4%|▍         | 2/47 [00:09<02:50,  3.79s/it]
Feature Extraction:   6%|▋         | 3/47 [00:09<01:33,  2.12s/it]
Feature Extraction:  15%|█▍        | 7/47 [00:09<00:24,  1.63it/s]
Feature Extraction:  19%|█▉        | 9/47 [00:09<00:16,  2.34it/s]
Feature Extraction:  23%|██▎       | 11/47 [00:09<00:12,  2.82it/s]
Feature Extraction:  28%|██▊       | 13/47 [00:10<00:10,  3.30it/s]
Feature Extraction:  30%|██▉       | 14/47 [00:18<00:57,  1.74s/it]
Feature Extraction:  32%|███▏      | 15/47 [00:18<00:46,  1.45s/it]
Feature Extraction:  34%|███▍      | 16/47 [00:18<00:35,  1.15s/it]
Feature Extraction:  36%|███▌      | 17/47 [00:18<00:26,  1.11it/s]
Feature Extraction:  40%|████      | 19/47 [00:19<00:16,  1.74it/s]
Feature Extraction:  45%|████▍     | 21/47 [00:19<00:11,  2.28it/s]
Feature Extraction:  49%|████▉     | 23/47 [00:19<00:07,  3.07it/s]
Feature Extraction:  51%|█████     | 24/47 [00:19<00:06,  3.55it/s]
Feature Extraction:  53%|█████▎    | 25/47 [00:20<00:06,  3.42it/s]
Feature Extraction:  55%|█████▌    | 26/47 [00:20<00:05,  3.68it/s]
Feature Extraction:  57%|█████▋    | 27/47 [00:27<00:41,  2.09s/it]
Feature Extraction:  60%|█████▉    | 28/47 [00:28<00:29,  1.57s/it]
Feature Extraction:  62%|██████▏   | 29/47 [00:28<00:21,  1.21s/it]
Feature Extraction:  64%|██████▍   | 30/47 [00:28<00:16,  1.04it/s]
Feature Extraction:  66%|██████▌   | 31/47 [00:28<00:11,  1.36it/s]
Feature Extraction:  68%|██████▊   | 32/47 [00:29<00:08,  1.69it/s]
Feature Extraction:  72%|███████▏  | 34/47 [00:29<00:04,  2.67it/s]
Feature Extraction:  74%|███████▍  | 35/47 [00:29<00:03,  3.01it/s]
Feature Extraction:  79%|███████▊  | 37/47 [00:29<00:02,  3.67it/s]
Feature Extraction:  83%|████████▎ | 39/47 [00:30<00:02,  3.86it/s]
Feature Extraction:  85%|████████▌ | 40/47 [00:34<00:07,  1.02s/it]
Feature Extraction:  87%|████████▋ | 41/47 [00:35<00:06,  1.13s/it]
Feature Extraction:  89%|████████▉ | 42/47 [00:35<00:04,  1.11it/s]
Feature Extraction:  91%|█████████▏| 43/47 [00:36<00:02,  1.35it/s]
Feature Extraction:  94%|█████████▎| 44/47 [00:36<00:01,  1.68it/s]
Feature Extraction:  96%|█████████▌| 45/47 [00:36<00:01,  1.94it/s]
Feature Extraction: 100%|██████████| 47/47 [00:36<00:00,  3.06it/s]
Feature Extraction: 100%|██████████| 47/47 [00:36<00:00,  1.27it/s]
Dependency not available for matrix_profile, this feature will be disabled!

Feature Extraction:   0%|          | 0/47 [00:00<?, ?it/s]
Feature Extraction:   2%|▏         | 1/47 [00:08<06:23,  8.35s/it]
Feature Extraction:   4%|▍         | 2/47 [00:08<02:38,  3.53s/it]
Feature Extraction:   6%|▋         | 3/47 [00:08<01:28,  2.02s/it]
Feature Extraction:  11%|█         | 5/47 [00:08<00:39,  1.07it/s]
Feature Extraction:  13%|█▎        | 6/47 [00:09<00:28,  1.42it/s]
Feature Extraction:  15%|█▍        | 7/47 [00:09<00:22,  1.74it/s]
Feature Extraction:  21%|██▏       | 10/47 [00:09<00:10,  3.48it/s]
Feature Extraction:  23%|██▎       | 11/47 [00:09<00:10,  3.38it/s]
Feature Extraction:  28%|██▊       | 13/47 [00:10<00:08,  3.96it/s]
Feature Extraction:  30%|██▉       | 14/47 [00:16<00:47,  1.44s/it]
Feature Extraction:  32%|███▏      | 15/47 [00:18<00:50,  1.56s/it]
Feature Extraction:  34%|███▍      | 16/47 [00:18<00:37,  1.22s/it]
Feature Extraction:  36%|███▌      | 17/47 [00:18<00:29,  1.01it/s]
Feature Extraction:  38%|███▊      | 18/47 [00:18<00:22,  1.30it/s]
Feature Extraction:  43%|████▎     | 20/47 [00:19<00:13,  1.99it/s]
Feature Extraction:  47%|████▋     | 22/47 [00:19<00:09,  2.60it/s]
Feature Extraction:  49%|████▉     | 23/47 [00:19<00:08,  2.85it/s]
Feature Extraction:  53%|█████▎    | 25/47 [00:20<00:06,  3.42it/s]
Feature Extraction:  55%|█████▌    | 26/47 [00:20<00:05,  3.68it/s]
Feature Extraction:  57%|█████▋    | 27/47 [00:25<00:27,  1.38s/it]
Feature Extraction:  60%|█████▉    | 28/47 [00:27<00:31,  1.63s/it]
Feature Extraction:  62%|██████▏   | 29/47 [00:27<00:22,  1.25s/it]
Feature Extraction:  64%|██████▍   | 30/47 [00:28<00:17,  1.03s/it]
Feature Extraction:  66%|██████▌   | 31/47 [00:28<00:13,  1.19it/s]
Feature Extraction:  68%|██████▊   | 32/47 [00:28<00:09,  1.58it/s]
Feature Extraction:  70%|███████   | 33/47 [00:28<00:07,  1.96it/s]
Feature Extraction:  72%|███████▏  | 34/47 [00:29<00:05,  2.19it/s]
Feature Extraction:  77%|███████▋  | 36/47 [00:29<00:03,  3.22it/s]
Feature Extraction:  79%|███████▊  | 37/47 [00:29<00:03,  3.25it/s]
Feature Extraction:  81%|████████  | 38/47 [00:30<00:02,  3.36it/s]
Feature Extraction:  83%|████████▎ | 39/47 [00:30<00:02,  3.43it/s]
Feature Extraction:  85%|████████▌ | 40/47 [00:34<00:09,  1.34s/it]
Feature Extraction:  89%|████████▉ | 42/47 [00:35<00:04,  1.07it/s]
Feature Extraction:  91%|█████████▏| 43/47 [00:35<00:03,  1.29it/s]
Feature Extraction:  94%|█████████▎| 44/47 [00:36<00:02,  1.27it/s]
Feature Extraction:  98%|█████████▊| 46/47 [00:36<00:00,  1.88it/s]
Feature Extraction: 100%|██████████| 47/47 [00:37<00:00,  2.03it/s]
Feature Extraction: 100%|██████████| 47/47 [00:37<00:00,  1.27it/s]
Dependency not available for matrix_profile, this feature will be disabled!

Feature Extraction:   0%|          | 0/47 [00:00<?, ?it/s]
Feature Extraction:   2%|▏         | 1/47 [00:08<06:50,  8.92s/it]
Feature Extraction:   4%|▍         | 2/47 [00:09<02:54,  3.87s/it]
Feature Extraction:  13%|█▎        | 6/47 [00:09<00:37,  1.10it/s]
Feature Extraction:  19%|█▉        | 9/47 [00:09<00:19,  1.94it/s]
Feature Extraction:  26%|██▌       | 12/47 [00:09<00:12,  2.86it/s]
Feature Extraction:  30%|██▉       | 14/47 [00:18<00:47,  1.43s/it]
Feature Extraction:  38%|███▊      | 18/47 [00:18<00:24,  1.20it/s]
Feature Extraction:  43%|████▎     | 20/47 [00:18<00:17,  1.52it/s]
Feature Extraction:  47%|████▋     | 22/47 [00:19<00:13,  1.90it/s]
Feature Extraction:  51%|█████     | 24/47 [00:19<00:09,  2.35it/s]
Feature Extraction:  53%|█████▎    | 25/47 [00:19<00:08,  2.49it/s]
Feature Extraction:  55%|█████▌    | 26/47 [00:20<00:08,  2.56it/s]
Feature Extraction:  57%|█████▋    | 27/47 [00:27<00:38,  1.94s/it]
Feature Extraction:  60%|█████▉    | 28/47 [00:28<00:30,  1.60s/it]
Feature Extraction:  64%|██████▍   | 30/47 [00:28<00:16,  1.00it/s]
Feature Extraction:  66%|██████▌   | 31/47 [00:28<00:12,  1.24it/s]
Feature Extraction:  68%|██████▊   | 32/47 [00:28<00:09,  1.51it/s]
Feature Extraction:  77%|███████▋  | 36/47 [00:28<00:03,  3.33it/s]
Feature Extraction:  81%|████████  | 38/47 [00:29<00:02,  3.76it/s]
Feature Extraction:  85%|████████▌ | 40/47 [00:34<00:06,  1.05it/s]
Feature Extraction:  87%|████████▋ | 41/47 [00:35<00:05,  1.10it/s]
Feature Extraction:  89%|████████▉ | 42/47 [00:35<00:04,  1.22it/s]
Feature Extraction:  91%|█████████▏| 43/47 [00:35<00:02,  1.52it/s]
Feature Extraction:  94%|█████████▎| 44/47 [00:36<00:01,  1.75it/s]
Feature Extraction:  96%|█████████▌| 45/47 [00:36<00:00,  2.21it/s]
Feature Extraction: 100%|██████████| 47/47 [00:36<00:00,  3.12it/s]
Feature Extraction: 100%|██████████| 47/47 [00:36<00:00,  1.29it/s]
Dependency not available for matrix_profile, this feature will be disabled!

Feature Extraction:   0%|          | 0/49 [00:00<?, ?it/s]
Feature Extraction:   2%|▏         | 1/49 [00:08<06:58,  8.72s/it]
Feature Extraction:   6%|▌         | 3/49 [00:08<01:46,  2.31s/it]
Feature Extraction:   8%|▊         | 4/49 [00:09<01:13,  1.62s/it]
Feature Extraction:  14%|█▍        | 7/49 [00:09<00:28,  1.46it/s]
Feature Extraction:  18%|█▊        | 9/49 [00:09<00:20,  1.92it/s]
Feature Extraction:  24%|██▍       | 12/49 [00:10<00:12,  3.00it/s]
Feature Extraction:  27%|██▋       | 13/49 [00:10<00:11,  3.10it/s]
Feature Extraction:  29%|██▊       | 14/49 [00:18<01:02,  1.77s/it]
Feature Extraction:  31%|███       | 15/49 [00:18<00:48,  1.43s/it]
Feature Extraction:  33%|███▎      | 16/49 [00:18<00:36,  1.12s/it]
Feature Extraction:  35%|███▍      | 17/49 [00:18<00:28,  1.11it/s]
Feature Extraction:  39%|███▉      | 19/49 [00:18<00:17,  1.69it/s]
Feature Extraction:  41%|████      | 20/49 [00:19<00:15,  1.84it/s]
Feature Extraction:  43%|████▎     | 21/49 [00:19<00:12,  2.26it/s]
Feature Extraction:  47%|████▋     | 23/49 [00:19<00:09,  2.81it/s]
Feature Extraction:  53%|█████▎    | 26/49 [00:20<00:07,  2.96it/s]
Feature Extraction:  55%|█████▌    | 27/49 [00:26<00:29,  1.35s/it]
Feature Extraction:  57%|█████▋    | 28/49 [00:27<00:26,  1.28s/it]
Feature Extraction:  59%|█████▉    | 29/49 [00:27<00:20,  1.03s/it]
Feature Extraction:  61%|██████    | 30/49 [00:28<00:15,  1.20it/s]
Feature Extraction:  63%|██████▎   | 31/49 [00:28<00:11,  1.51it/s]
Feature Extraction:  65%|██████▌   | 32/49 [00:29<00:11,  1.49it/s]
Feature Extraction:  67%|██████▋   | 33/49 [00:29<00:08,  1.95it/s]
Feature Extraction:  69%|██████▉   | 34/49 [00:29<00:05,  2.53it/s]
Feature Extraction:  71%|███████▏  | 35/49 [00:29<00:04,  3.12it/s]
Feature Extraction:  73%|███████▎  | 36/49 [00:29<00:04,  3.19it/s]
Feature Extraction:  78%|███████▊  | 38/49 [00:29<00:02,  4.39it/s]
Feature Extraction:  80%|███████▉  | 39/49 [00:30<00:04,  2.46it/s]
Feature Extraction:  82%|████████▏ | 40/49 [00:35<00:13,  1.52s/it]
Feature Extraction:  84%|████████▎ | 41/49 [00:35<00:09,  1.16s/it]
Feature Extraction:  86%|████████▌ | 42/49 [00:35<00:06,  1.15it/s]
Feature Extraction:  88%|████████▊ | 43/49 [00:36<00:04,  1.27it/s]
Feature Extraction:  90%|████████▉ | 44/49 [00:36<00:03,  1.45it/s]
Feature Extraction:  92%|█████████▏| 45/49 [00:37<00:02,  1.75it/s]
Feature Extraction:  96%|█████████▌| 47/49 [00:37<00:00,  2.14it/s]
Feature Extraction:  98%|█████████▊| 48/49 [00:38<00:00,  2.64it/s]
Feature Extraction: 100%|██████████| 49/49 [00:38<00:00,  1.29it/s]
Dependency not available for matrix_profile, this feature will be disabled!

Feature Extraction:   0%|          | 0/47 [00:00<?, ?it/s]
Feature Extraction:   2%|▏         | 1/47 [00:08<06:31,  8.51s/it]
Feature Extraction:   4%|▍         | 2/47 [00:08<02:50,  3.79s/it]
Feature Extraction:  13%|█▎        | 6/47 [00:09<00:36,  1.12it/s]
Feature Extraction:  17%|█▋        | 8/47 [00:09<00:23,  1.65it/s]
Feature Extraction:  23%|██▎       | 11/47 [00:09<00:13,  2.71it/s]
Feature Extraction:  28%|██▊       | 13/47 [00:09<00:10,  3.31it/s]
Feature Extraction:  32%|███▏      | 15/47 [00:18<00:46,  1.46s/it]
Feature Extraction:  36%|███▌      | 17/47 [00:18<00:31,  1.05s/it]
Feature Extraction:  40%|████      | 19/47 [00:18<00:21,  1.29it/s]
Feature Extraction:  45%|████▍     | 21/47 [00:19<00:15,  1.66it/s]
Feature Extraction:  51%|█████     | 24/47 [00:19<00:11,  2.03it/s]
Feature Extraction:  55%|█████▌    | 26/47 [00:20<00:08,  2.39it/s]
Feature Extraction:  57%|█████▋    | 27/47 [00:26<00:28,  1.40s/it]
Feature Extraction:  60%|█████▉    | 28/47 [00:27<00:25,  1.34s/it]
Feature Extraction:  64%|██████▍   | 30/47 [00:28<00:15,  1.08it/s]
Feature Extraction:  68%|██████▊   | 32/47 [00:28<00:09,  1.52it/s]
Feature Extraction:  72%|███████▏  | 34/47 [00:28<00:06,  2.13it/s]
Feature Extraction:  77%|███████▋  | 36/47 [00:28<00:04,  2.72it/s]
Feature Extraction:  79%|███████▊  | 37/47 [00:29<00:04,  2.34it/s]
Feature Extraction:  81%|████████  | 38/47 [00:30<00:03,  2.35it/s]
Feature Extraction:  83%|████████▎ | 39/47 [00:30<00:03,  2.29it/s]
Feature Extraction:  85%|████████▌ | 40/47 [00:34<00:08,  1.27s/it]
Feature Extraction:  87%|████████▋ | 41/47 [00:34<00:06,  1.01s/it]
Feature Extraction:  89%|████████▉ | 42/47 [00:35<00:05,  1.03s/it]
Feature Extraction:  91%|█████████▏| 43/47 [00:36<00:03,  1.15it/s]
Feature Extraction:  96%|█████████▌| 45/47 [00:36<00:01,  1.91it/s]
Feature Extraction: 100%|██████████| 47/47 [00:36<00:00,  2.25it/s]
Feature Extraction: 100%|██████████| 47/47 [00:36<00:00,  1.27it/s]
Dependency not available for matrix_profile, this feature will be disabled!

Feature Extraction:   0%|          | 0/49 [00:00<?, ?it/s]
Feature Extraction:   2%|▏         | 1/49 [00:08<06:54,  8.63s/it]
Feature Extraction:   4%|▍         | 2/49 [00:09<02:59,  3.81s/it]
Feature Extraction:   8%|▊         | 4/49 [00:09<01:07,  1.50s/it]
Feature Extraction:  12%|█▏        | 6/49 [00:09<00:38,  1.13it/s]
Feature Extraction:  18%|█▊        | 9/49 [00:09<00:18,  2.17it/s]
Feature Extraction:  22%|██▏       | 11/49 [00:10<00:13,  2.87it/s]
Feature Extraction:  27%|██▋       | 13/49 [00:10<00:09,  3.78it/s]
Feature Extraction:  31%|███       | 15/49 [00:17<00:47,  1.38s/it]
Feature Extraction:  33%|███▎      | 16/49 [00:18<00:41,  1.26s/it]
Feature Extraction:  39%|███▉      | 19/49 [00:18<00:22,  1.35it/s]
Feature Extraction:  41%|████      | 20/49 [00:18<00:18,  1.58it/s]
Feature Extraction:  43%|████▎     | 21/49 [00:19<00:15,  1.81it/s]
Feature Extraction:  49%|████▉     | 24/49 [00:19<00:10,  2.43it/s]
Feature Extraction:  51%|█████     | 25/49 [00:20<00:10,  2.37it/s]
Feature Extraction:  53%|█████▎    | 26/49 [00:21<00:11,  2.08it/s]
Feature Extraction:  55%|█████▌    | 27/49 [00:26<00:34,  1.56s/it]
Feature Extraction:  57%|█████▋    | 28/49 [00:27<00:29,  1.39s/it]
Feature Extraction:  59%|█████▉    | 29/49 [00:27<00:22,  1.12s/it]
Feature Extraction:  61%|██████    | 30/49 [00:27<00:16,  1.13it/s]
Feature Extraction:  63%|██████▎   | 31/49 [00:27<00:12,  1.49it/s]
Feature Extraction:  65%|██████▌   | 32/49 [00:28<00:10,  1.63it/s]
Feature Extraction:  67%|██████▋   | 33/49 [00:29<00:09,  1.63it/s]
Feature Extraction:  69%|██████▉   | 34/49 [00:29<00:07,  2.06it/s]
Feature Extraction:  71%|███████▏  | 35/49 [00:29<00:06,  2.14it/s]
Feature Extraction:  76%|███████▌  | 37/49 [00:29<00:03,  3.55it/s]
Feature Extraction:  78%|███████▊  | 38/49 [00:30<00:03,  3.45it/s]
Feature Extraction:  80%|███████▉  | 39/49 [00:31<00:06,  1.54it/s]
Feature Extraction:  82%|████████▏ | 40/49 [00:34<00:11,  1.27s/it]
Feature Extraction:  84%|████████▎ | 41/49 [00:35<00:08,  1.10s/it]
Feature Extraction:  86%|████████▌ | 42/49 [00:36<00:07,  1.06s/it]
Feature Extraction:  88%|████████▊ | 43/49 [00:36<00:04,  1.26it/s]
Feature Extraction:  92%|█████████▏| 45/49 [00:37<00:02,  1.50it/s]
Feature Extraction:  98%|█████████▊| 48/49 [00:37<00:00,  2.68it/s]
Feature Extraction: 100%|██████████| 49/49 [00:37<00:00,  3.02it/s]
Feature Extraction: 100%|██████████| 49/49 [00:37<00:00,  1.29it/s]
imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-12.0-15.0
train
(101, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
512  Pilot02          3  linreg  ...  -6.796172        0.051448      0.069456
513  Pilot02          3  linreg  ...  -9.129009        0.001051      0.970434
514  Pilot02          3  linreg  ...  -5.420812       -0.014440      0.610586
515  Pilot02          3  linreg  ... -25.639528       -0.037107      0.190544
516  Pilot03          2  linreg  ...  -1.298246       -0.065345      0.041042

[517 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-12.0-17.0
train
(100, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
513  Pilot02          3  linreg  ...  -9.129009        0.001051      0.970434
514  Pilot02          3  linreg  ...  -5.420812       -0.014440      0.610586
515  Pilot02          3  linreg  ... -25.639528       -0.037107      0.190544
516  Pilot03          2  linreg  ...  -1.298246       -0.065345      0.041042
517  Pilot03          2  linreg  ...  -1.320072       -0.068867      0.031281

[518 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-12.0-20.0
train
(101, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
514  Pilot02          3  linreg  ...  -5.420812       -0.014440      0.610586
515  Pilot02          3  linreg  ... -25.639528       -0.037107      0.190544
516  Pilot03          2  linreg  ...  -1.298246       -0.065345      0.041042
517  Pilot03          2  linreg  ...  -1.320072       -0.068867      0.031281
518  Pilot03          2  linreg  ...  -1.719100       -0.014930      0.640971

[519 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-15.0-17.0
train
(101, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
515  Pilot02          3  linreg  ... -25.639528       -0.037107      0.190544
516  Pilot03          2  linreg  ...  -1.298246       -0.065345      0.041042
517  Pilot03          2  linreg  ...  -1.320072       -0.068867      0.031281
518  Pilot03          2  linreg  ...  -1.719100       -0.014930      0.640971
519  Pilot03          2  linreg  ...  -1.205096       -0.094689      0.003036

[520 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-15.0-20.0
train
(102, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
516  Pilot03          2  linreg  ...  -1.298246       -0.065345      0.041042
517  Pilot03          2  linreg  ...  -1.320072       -0.068867      0.031281
518  Pilot03          2  linreg  ...  -1.719100       -0.014930      0.640971
519  Pilot03          2  linreg  ...  -1.205096       -0.094689      0.003036
520  Pilot03          2  linreg  ...  -1.369422       -0.058643      0.066776

[521 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-7.0-10.0-17.0-20.0
train
(101, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
517  Pilot03          2  linreg  ...  -1.320072       -0.068867      0.031281
518  Pilot03          2  linreg  ...  -1.719100       -0.014930      0.640971
519  Pilot03          2  linreg  ...  -1.205096       -0.094689      0.003036
520  Pilot03          2  linreg  ...  -1.369422       -0.058643      0.066776
521  Pilot03          2  linreg  ...  -1.410067       -0.043944      0.169702

[522 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-7.0-12.0-15.0-17.0
train
(101, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
518  Pilot03          2  linreg  ...  -1.719100       -0.014930      0.640971
519  Pilot03          2  linreg  ...  -1.205096       -0.094689      0.003036
520  Pilot03          2  linreg  ...  -1.369422       -0.058643      0.066776
521  Pilot03          2  linreg  ...  -1.410067       -0.043944      0.169702
522  Pilot03          2  linreg  ...  -1.209088       -0.069918      0.028784

[523 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-7.0-12.0-15.0-20.0
train
(102, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
519  Pilot03          2  linreg  ...  -1.205096       -0.094689      0.003036
520  Pilot03          2  linreg  ...  -1.369422       -0.058643      0.066776
521  Pilot03          2  linreg  ...  -1.410067       -0.043944      0.169702
522  Pilot03          2  linreg  ...  -1.209088       -0.069918      0.028784
523  Pilot03          2  linreg  ...  -1.500180       -0.038757      0.225913

[524 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-7.0-12.0-17.0-20.0
train
(101, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
520  Pilot03          2  linreg  ...  -1.369422       -0.058643      0.066776
521  Pilot03          2  linreg  ...  -1.410067       -0.043944      0.169702
522  Pilot03          2  linreg  ...  -1.209088       -0.069918      0.028784
523  Pilot03          2  linreg  ...  -1.500180       -0.038757      0.225913
524  Pilot03          2  linreg  ...  -1.486533       -0.028625      0.371199

[525 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-7.0-15.0-17.0-20.0
train
(102, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
521  Pilot03          2  linreg  ...  -1.410067       -0.043944      0.169702
522  Pilot03          2  linreg  ...  -1.209088       -0.069918      0.028784
523  Pilot03          2  linreg  ...  -1.500180       -0.038757      0.225913
524  Pilot03          2  linreg  ...  -1.486533       -0.028625      0.371199
525  Pilot03          2  linreg  ...  -1.234225       -0.050201      0.116671

[526 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-10.0-12.0-15.0-17.0
train
(101, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
522  Pilot03          2  linreg  ...  -1.209088       -0.069918      0.028784
523  Pilot03          2  linreg  ...  -1.500180       -0.038757      0.225913
524  Pilot03          2  linreg  ...  -1.486533       -0.028625      0.371199
525  Pilot03          2  linreg  ...  -1.234225       -0.050201      0.116671
526  Pilot03          2  linreg  ...  -0.895766       -0.081948      0.010353

[527 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-10.0-12.0-15.0-20.0
train
(102, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
523  Pilot03          2  linreg  ...  -1.500180       -0.038757      0.225913
524  Pilot03          2  linreg  ...  -1.486533       -0.028625      0.371199
525  Pilot03          2  linreg  ...  -1.234225       -0.050201      0.116671
526  Pilot03          2  linreg  ...  -0.895766       -0.081948      0.010353
527  Pilot03          2  linreg  ...  -1.147796       -0.053428      0.094935

[528 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-10.0-12.0-17.0-20.0
train
(101, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
524  Pilot03          2  linreg  ...  -1.486533       -0.028625      0.371199
525  Pilot03          2  linreg  ...  -1.234225       -0.050201      0.116671
526  Pilot03          2  linreg  ...  -0.895766       -0.081948      0.010353
527  Pilot03          2  linreg  ...  -1.147796       -0.053428      0.094935
528  Pilot03          2  linreg  ...  -1.169716       -0.041156      0.198449

[529 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-10.0-15.0-17.0-20.0
train
(102, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
525  Pilot03          2  linreg  ...  -1.234225       -0.050201      0.116671
526  Pilot03          2  linreg  ...  -0.895766       -0.081948      0.010353
527  Pilot03          2  linreg  ...  -1.147796       -0.053428      0.094935
528  Pilot03          2  linreg  ...  -1.169716       -0.041156      0.198449
529  Pilot03          2  linreg  ...  -0.941939       -0.074300      0.020135

[530 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi5.0-12.0-15.0-17.0-20.0
train
(102, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
526  Pilot03          2  linreg  ...  -0.895766       -0.081948      0.010353
527  Pilot03          2  linreg  ...  -1.147796       -0.053428      0.094935
528  Pilot03          2  linreg  ...  -1.169716       -0.041156      0.198449
529  Pilot03          2  linreg  ...  -0.941939       -0.074300      0.020135
530  Pilot03          2  linreg  ...  -0.999938       -0.044756      0.161942

[531 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi7.0-10.0-12.0-15.0-17.0
train
(101, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
527  Pilot03          2  linreg  ...  -1.147796       -0.053428      0.094935
528  Pilot03          2  linreg  ...  -1.169716       -0.041156      0.198449
529  Pilot03          2  linreg  ...  -0.941939       -0.074300      0.020135
530  Pilot03          2  linreg  ...  -0.999938       -0.044756      0.161942
531  Pilot03          2  linreg  ...  -0.445521       -0.103372      0.001207

[532 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi7.0-10.0-12.0-15.0-20.0
train
(102, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
528  Pilot03          2  linreg  ...  -1.169716       -0.041156      0.198449
529  Pilot03          2  linreg  ...  -0.941939       -0.074300      0.020135
530  Pilot03          2  linreg  ...  -0.999938       -0.044756      0.161942
531  Pilot03          2  linreg  ...  -0.445521       -0.103372      0.001207
532  Pilot03          2  linreg  ...  -0.629643       -0.066178      0.038526

[533 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi7.0-10.0-12.0-17.0-20.0
train
(101, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
529  Pilot03          2  linreg  ...  -0.941939       -0.074300      0.020135
530  Pilot03          2  linreg  ...  -0.999938       -0.044756      0.161942
531  Pilot03          2  linreg  ...  -0.445521       -0.103372      0.001207
532  Pilot03          2  linreg  ...  -0.629643       -0.066178      0.038526
533  Pilot03          2  linreg  ...  -0.683093       -0.060810      0.057299

[534 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi7.0-10.0-15.0-17.0-20.0
train
(102, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
530  Pilot03          2  linreg  ...  -0.999938       -0.044756      0.161942
531  Pilot03          2  linreg  ...  -0.445521       -0.103372      0.001207
532  Pilot03          2  linreg  ...  -0.629643       -0.066178      0.038526
533  Pilot03          2  linreg  ...  -0.683093       -0.060810      0.057299
534  Pilot03          2  linreg  ...  -0.579251       -0.067470      0.034885

[535 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi7.0-12.0-15.0-17.0-20.0
train
(102, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
531  Pilot03          2  linreg  ...  -0.445521       -0.103372      0.001207
532  Pilot03          2  linreg  ...  -0.629643       -0.066178      0.038526
533  Pilot03          2  linreg  ...  -0.683093       -0.060810      0.057299
534  Pilot03          2  linreg  ...  -0.579251       -0.067470      0.034885
535  Pilot03          2  linreg  ...  -0.584314       -0.068252      0.032827

[536 rows x 18 columns]
imu-bvp_rr_Pilot03_id2_combi10.0-12.0-15.0-17.0-20.0
train
(102, 5485)
test
(978, 5484)
---LinearRegression---
adding new entry
     subject  config_id mdl_str  ...         r2  pearsonr_coeff pearsonr_pval
0    Pilot02          0  linreg  ...  -9.864563        0.038776      0.364940
1    Pilot02          0  linreg  ... -11.875765        0.070097      0.101171
2    Pilot02          0  linreg  ... -11.069278        0.047023      0.271822
3    Pilot02          0  linreg  ... -25.345517        0.016892      0.693177
4    Pilot02          0  linreg  ... -15.299470        0.118749      0.005380
..       ...        ...     ...  ...        ...             ...           ...
532  Pilot03          2  linreg  ...  -0.629643       -0.066178      0.038526
533  Pilot03          2  linreg  ...  -0.683093       -0.060810      0.057299
534  Pilot03          2  linreg  ...  -0.579251       -0.067470      0.034885
535  Pilot03          2  linreg  ...  -0.584314       -0.068252      0.032827
536  Pilot03          2  linreg  ...  -0.325231       -0.063084      0.048580

[537 rows x 18 columns]
Namespace(data_input='imu-bvp', feature_method='tsfresh', lbl_str='pss', model='linreg', overwrite=1, subject=3, test_standing=1, train_len=5, win_shift=0.2, win_size=12)