2025-11-06 13:42:52.287644: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:42:52.299538: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762432972.313508 1345472 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762432972.317743 1345472 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762432972.328242 1345472 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762432972.328264 1345472 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762432972.328266 1345472 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762432972.328268 1345472 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:42:52.331518: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/tune/impl/tuner_internal.py:144: RayDeprecationWarning: The `RunConfig` class should be imported from `ray.tune` when passing it to the Tuner. Please update your imports. See this issue for more context and migration options: https://github.com/ray-project/ray/issues/49454. Disable these warnings by setting the environment variable: RAY_TRAIN_ENABLE_V2_MIGRATION_WARNINGS=0
  _log_deprecation_warning(
2025-11-06 13:42:57,161	INFO worker.py:1927 -- Started a local Ray instance.
2025-11-06 13:42:57,826	INFO tune.py:253 -- Initializing Ray automatically. For cluster usage or custom Ray initialization, call `ray.init(...)` before `Tuner(...)`.
2025-11-06 13:42:57,891	INFO trial.py:182 -- Creating a new dirname dir_1f587_a966 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,894	INFO trial.py:182 -- Creating a new dirname dir_1f587_f874 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,896	INFO trial.py:182 -- Creating a new dirname dir_1f587_d244 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,899	INFO trial.py:182 -- Creating a new dirname dir_1f587_cec8 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,901	INFO trial.py:182 -- Creating a new dirname dir_1f587_180d because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,903	INFO trial.py:182 -- Creating a new dirname dir_1f587_9499 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,906	INFO trial.py:182 -- Creating a new dirname dir_1f587_411c because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,908	INFO trial.py:182 -- Creating a new dirname dir_1f587_d188 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,911	INFO trial.py:182 -- Creating a new dirname dir_1f587_6af4 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,913	INFO trial.py:182 -- Creating a new dirname dir_1f587_d719 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,916	INFO trial.py:182 -- Creating a new dirname dir_1f587_1003 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,919	INFO trial.py:182 -- Creating a new dirname dir_1f587_f35b because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,922	INFO trial.py:182 -- Creating a new dirname dir_1f587_9bf1 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,927	INFO trial.py:182 -- Creating a new dirname dir_1f587_a41c because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,931	INFO trial.py:182 -- Creating a new dirname dir_1f587_b581 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,937	INFO trial.py:182 -- Creating a new dirname dir_1f587_16e6 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,941	INFO trial.py:182 -- Creating a new dirname dir_1f587_0766 because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,945	INFO trial.py:182 -- Creating a new dirname dir_1f587_a1ab because trial dirname 'dir_1f587' already exists.
2025-11-06 13:42:57,953	INFO trial.py:182 -- Creating a new dirname dir_1f587_bddd because trial dirname 'dir_1f587' already exists.
1 GPU(s) detected and VRAM set to crossover mode..
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Training a non-convolutional model.
Se lanza la búsqueda de hiperparámetros óptimos del modelo
╭──────────────────────────────────────────────────────────────────────╮
│ Configuration for experiment     BalancedRF_hyperparameters_tuning   │
├──────────────────────────────────────────────────────────────────────┤
│ Search algorithm                 BasicVariantGenerator               │
│ Scheduler                        AsyncHyperBandScheduler             │
│ Number of trials                 20                                  │
╰──────────────────────────────────────────────────────────────────────╯

View detailed results here: /mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_PI/case_PI_BRF_acc_superclasses_CPA_METs/BalancedRF_hyperparameters_tuning
To visualize your results with TensorBoard, run: `tensorboard --logdir /tmp/ray/session_2025-11-06_13-42-56_361956_1345472/artifacts/2025-11-06_13-42-57/BalancedRF_hyperparameters_tuning/driver_artifacts`

Trial status: 20 PENDING
Current time: 2025-11-06 13:42:58. Total running time: 0s
Logical resource usage: 0/20 CPUs, 0/1 GPUs (0.0/1.0 accelerator_type:G)
╭─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ Trial name     status       n_estimators     max_depth     min_samples_split     min_samples_leaf   max_features       random_state │
├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ trial_1f587    PENDING               343             5                    38                   23   0.3                        4593 │
│ trial_1f587    PENDING               315             7                    35                   11   0.3                        8746 │
│ trial_1f587    PENDING               383             6                    52                   19   sqrt                       8793 │
│ trial_1f587    PENDING               364             6                    37                   28   sqrt                       5587 │
│ trial_1f587    PENDING               251             5                    25                   19   0.3                        6804 │
│ trial_1f587    PENDING               244             5                    49                   20   0.3                        5539 │
│ trial_1f587    PENDING               264             6                    50                   18   0.3                        2156 │
│ trial_1f587    PENDING               297             6                    50                   24   sqrt                       9411 │
│ trial_1f587    PENDING               339             5                    49                   11   0.3                        3702 │
│ trial_1f587    PENDING               496             7                    35                   10   0.3                        2487 │
│ trial_1f587    PENDING               365             7                    52                   22   0.3                        2153 │
│ trial_1f587    PENDING               237             5                    26                   14   0.3                        4625 │
│ trial_1f587    PENDING               203             7                    53                   12   0.3                        9522 │
│ trial_1f587    PENDING               345             7                    32                   16   0.3                        8453 │
│ trial_1f587    PENDING               276             5                    26                   20   sqrt                         52 │
│ trial_1f587    PENDING               228             6                    40                   17   0.3                        6817 │
│ trial_1f587    PENDING               447             5                    41                   11   0.3                        5629 │
│ trial_1f587    PENDING               469             7                    52                   23   0.3                        9185 │
│ trial_1f587    PENDING               255             6                    37                   20   sqrt                       7491 │
│ trial_1f587    PENDING               314             5                    59                   19   0.3                        1912 │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       6 │
│ max_features                 sqrt │
│ min_samples_leaf               19 │
│ min_samples_split              52 │
│ n_estimators                  383 │
│ random_state                 8793 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       7 │
│ max_features                  0.3 │
│ min_samples_leaf               12 │
│ min_samples_split              53 │
│ n_estimators                  203 │
│ random_state                 9522 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       5 │
│ max_features                  0.3 │
│ min_samples_leaf               23 │
│ min_samples_split              38 │
│ n_estimators                  343 │
│ random_state                 4593 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       6 │
│ max_features                 sqrt │
│ min_samples_leaf               28 │
│ min_samples_split              37 │
│ n_estimators                  364 │
│ random_state                 5587 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       6 │
│ max_features                 sqrt │
│ min_samples_leaf               20 │
│ min_samples_split              37 │
│ n_estimators                  255 │
│ random_state                 7491 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
[36m(train_brf_ray_tune pid=1347144)[0m 2025-11-06 13:43:01.065867: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
[36m(train_brf_ray_tune pid=1347144)[0m 2025-11-06 13:43:01.087372: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       5 │
│ max_features                  0.3 │
│ min_samples_leaf               19 │
│ min_samples_split              59 │
│ n_estimators                  314 │
│ random_state                 1912 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       5 │
│ max_features                  0.3 │
│ min_samples_leaf               14 │
│ min_samples_split              26 │
│ n_estimators                  237 │
│ random_state                 4625 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       5 │
│ max_features                  0.3 │
│ min_samples_leaf               19 │
│ min_samples_split              25 │
│ n_estimators                  251 │
│ random_state                 6804 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       7 │
│ max_features                  0.3 │
│ min_samples_leaf               10 │
│ min_samples_split              35 │
│ n_estimators                  496 │
│ random_state                 2487 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       7 │
│ max_features                  0.3 │
│ min_samples_leaf               23 │
│ min_samples_split              52 │
│ n_estimators                  469 │
│ random_state                 9185 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       7 │
│ max_features                  0.3 │
│ min_samples_leaf               16 │
│ min_samples_split              32 │
│ n_estimators                  345 │
│ random_state                 8453 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       6 │
│ max_features                 sqrt │
│ min_samples_leaf               24 │
│ min_samples_split              50 │
│ n_estimators                  297 │
│ random_state                 9411 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       6 │
│ max_features                  0.3 │
│ min_samples_leaf               17 │
│ min_samples_split              40 │
│ n_estimators                  228 │
│ random_state                 6817 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       7 │
│ max_features                  0.3 │
│ min_samples_leaf               11 │
│ min_samples_split              35 │
│ n_estimators                  315 │
│ random_state                 8746 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       6 │
│ max_features                  0.3 │
│ min_samples_leaf               18 │
│ min_samples_split              50 │
│ n_estimators                  264 │
│ random_state                 2156 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       5 │
│ max_features                  0.3 │
│ min_samples_leaf               20 │
│ min_samples_split              49 │
│ n_estimators                  244 │
│ random_state                 5539 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       5 │
│ max_features                  0.3 │
│ min_samples_leaf               11 │
│ min_samples_split              41 │
│ n_estimators                  447 │
│ random_state                 5629 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
[36m(train_brf_ray_tune pid=1347144)[0m WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
[36m(train_brf_ray_tune pid=1347144)[0m E0000 00:00:1762432981.115615 1348267 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
[36m(train_brf_ray_tune pid=1347144)[0m E0000 00:00:1762432981.123777 1348267 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
[36m(train_brf_ray_tune pid=1347144)[0m W0000 00:00:1762432981.142938 1348267 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
[36m(train_brf_ray_tune pid=1347144)[0m W0000 00:00:1762432981.142982 1348267 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
[36m(train_brf_ray_tune pid=1347144)[0m W0000 00:00:1762432981.142985 1348267 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
[36m(train_brf_ray_tune pid=1347144)[0m W0000 00:00:1762432981.142987 1348267 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
[36m(train_brf_ray_tune pid=1347144)[0m 2025-11-06 13:43:01.149261: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
[36m(train_brf_ray_tune pid=1347144)[0m To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
[36m(train_brf_ray_tune pid=1347144)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
[36m(train_brf_ray_tune pid=1347144)[0m   return fit_method(estimator, *args, **kwargs)
[36m(train_brf_ray_tune pid=1347144)[0m [Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[36m(train_brf_ray_tune pid=1347144)[0m [Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.2s
[36m(train_brf_ray_tune pid=1347146)[0m 2025-11-06 13:43:01.597448: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.[32m [repeated 19x across cluster] (Ray deduplicates logs by default. Set RAY_DEDUP_LOGS=0 to disable log deduplication, or see https://docs.ray.io/en/master/ray-observability/user-guides/configure-logging.html#log-deduplication for more options.)[0m
[36m(train_brf_ray_tune pid=1347146)[0m 2025-11-06 13:43:01.617697: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered[32m [repeated 19x across cluster][0m
[36m(train_brf_ray_tune pid=1347155)[0m WARNING: All log messages before absl::InitializeLog() is called are written to STDERR[32m [repeated 19x across cluster][0m
[36m(train_brf_ray_tune pid=1347155)[0m E0000 00:00:1762432981.685874 1348400 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered[32m [repeated 19x across cluster][0m
[36m(train_brf_ray_tune pid=1347155)[0m E0000 00:00:1762432981.694191 1348400 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered[32m [repeated 19x across cluster][0m
[36m(train_brf_ray_tune pid=1347146)[0m W0000 00:00:1762432981.681284 1348389 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.[32m [repeated 76x across cluster][0m
[36m(train_brf_ray_tune pid=1347146)[0m 2025-11-06 13:43:01.687128: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.[32m [repeated 19x across cluster][0m
[36m(train_brf_ray_tune pid=1347146)[0m To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.[32m [repeated 19x across cluster][0m
[36m(train_brf_ray_tune pid=1347146)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().[32m [repeated 19x across cluster][0m
[36m(train_brf_ray_tune pid=1347146)[0m   return fit_method(estimator, *args, **kwargs)[32m [repeated 19x across cluster][0m
[36m(train_brf_ray_tune pid=1347146)[0m [Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.[32m [repeated 19x across cluster][0m
[36m(train_brf_ray_tune pid=1347141)[0m [Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    5.5s[32m [repeated 20x across cluster][0m
[36m(train_brf_ray_tune pid=1347141)[0m [Parallel(n_jobs=-1)]: Done 255 out of 255 | elapsed:    9.7s finished
[36m(train_brf_ray_tune pid=1347141)[0m [Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[36m(train_brf_ray_tune pid=1347147)[0m [Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    9.9s[32m [repeated 5x across cluster][0m
[36m(train_brf_ray_tune pid=1347141)[0m [Parallel(n_jobs=20)]: Done 255 out of 255 | elapsed:    0.5s finished
[36m(train_brf_ray_tune pid=1347141)[0m [Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[36m(train_brf_ray_tune pid=1347141)[0m [Parallel(n_jobs=20)]: Done 255 out of 255 | elapsed:    0.5s finished
[36m(train_brf_ray_tune pid=1347141)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454
[36m(train_brf_ray_tune pid=1347141)[0m   _log_deprecation_warning(
[36m(train_brf_ray_tune pid=1347155)[0m [Parallel(n_jobs=-1)]: Done 276 out of 276 | elapsed:   14.1s finished
[36m(train_brf_ray_tune pid=1347133)[0m [Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:   14.2s[32m [repeated 13x across cluster][0m
[36m(train_brf_ray_tune pid=1347148)[0m [Parallel(n_jobs=-1)]: Done 251 out of 251 | elapsed:   16.2s finished
[36m(train_brf_ray_tune pid=1347155)[0m [Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[36m(train_brf_ray_tune pid=1347155)[0m [Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[36m(train_brf_ray_tune pid=1347155)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454
[36m(train_brf_ray_tune pid=1347155)[0m   _log_deprecation_warning(
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       5 │
│ max_features                  0.3 │
│ min_samples_leaf               11 │
│ min_samples_split              49 │
│ n_estimators                  339 │
│ random_state                 3702 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       7 │
│ max_features                  0.3 │
│ min_samples_leaf               22 │
│ min_samples_split              52 │
│ n_estimators                  365 │
│ random_state                 2153 │
╰───────────────────────────────────╯
Trial trial_1f587 started with configuration:
╭───────────────────────────────────╮
│ Trial trial_1f587 config          │
├───────────────────────────────────┤
│ max_depth                       5 │
│ max_features                 sqrt │
│ min_samples_leaf               20 │
│ min_samples_split              26 │
│ n_estimators                  276 │
│ random_state                   52 │
╰───────────────────────────────────╯

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:16. Total running time: 18s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             15.7922 │
│ time_total_s                 15.7922 │
│ training_iteration                 1 │
│ test_accuracy                0.77465 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:16. Total running time: 18s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:22. Total running time: 24s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             20.9063 │
│ time_total_s                 20.9063 │
│ training_iteration                 1 │
│ test_accuracy                0.77835 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:22. Total running time: 24s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:22. Total running time: 25s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             22.1202 │
│ time_total_s                 22.1202 │
│ training_iteration                 1 │
│ test_accuracy                0.76723 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:22. Total running time: 25s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:23. Total running time: 25s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             22.4998 │
│ time_total_s                 22.4998 │
│ training_iteration                 1 │
│ test_accuracy                 0.7917 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:23. Total running time: 25s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:23. Total running time: 25s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             22.6004 │
│ time_total_s                 22.6004 │
│ training_iteration                 1 │
│ test_accuracy                0.76798 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:23. Total running time: 25s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:24. Total running time: 26s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             23.8567 │
│ time_total_s                 23.8567 │
│ training_iteration                 1 │
│ test_accuracy                0.76798 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:24. Total running time: 26s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:24. Total running time: 26s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             24.0269 │
│ time_total_s                 24.0269 │
│ training_iteration                 1 │
│ test_accuracy                0.78428 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:24. Total running time: 26s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:24. Total running time: 26s
[36m(train_brf_ray_tune pid=1347150)[0m [Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.2s[32m [repeated 45x across cluster][0m
[36m(train_brf_ray_tune pid=1347134)[0m [Parallel(n_jobs=20)]: Done 343 out of 343 | elapsed:    0.3s finished[32m [repeated 30x across cluster][0m
[36m(train_brf_ray_tune pid=1347134)[0m [Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.[32m [repeated 20x across cluster][0m
[36m(train_brf_ray_tune pid=1347134)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 10x across cluster][0m
[36m(train_brf_ray_tune pid=1347134)[0m   _log_deprecation_warning([32m [repeated 10x across cluster][0m
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             23.8098 │
│ time_total_s                 23.8098 │
│ training_iteration                 1 │
│ test_accuracy                0.77094 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:24. Total running time: 26s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:24. Total running time: 27s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             24.1349 │
│ time_total_s                 24.1349 │
│ training_iteration                 1 │
│ test_accuracy                0.79763 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:24. Total running time: 27s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:25. Total running time: 27s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             24.0684 │
│ time_total_s                 24.0684 │
│ training_iteration                 1 │
│ test_accuracy                0.78577 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:25. Total running time: 27s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:25. Total running time: 27s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             24.6461 │
│ time_total_s                 24.6461 │
│ training_iteration                 1 │
│ test_accuracy                0.77984 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:25. Total running time: 27s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:26. Total running time: 28s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             25.5856 │
│ time_total_s                 25.5856 │
│ training_iteration                 1 │
│ test_accuracy                0.76575 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:26. Total running time: 28s

Trial status: 12 TERMINATED | 8 RUNNING
Current time: 2025-11-06 13:43:28. Total running time: 30s
Logical resource usage: 8.0/20 CPUs, 0/1 GPUs (0.0/1.0 accelerator_type:G)
╭─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ Trial name     status         n_estimators     max_depth     min_samples_split     min_samples_leaf   max_features       random_state     iter     total time (s)     test_accuracy │
├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ trial_1f587    RUNNING                 315             7                    35                   11   0.3                        8746                                               │
│ trial_1f587    RUNNING                 339             5                    49                   11   0.3                        3702                                               │
│ trial_1f587    RUNNING                 496             7                    35                   10   0.3                        2487                                               │
│ trial_1f587    RUNNING                 365             7                    52                   22   0.3                        2153                                               │
│ trial_1f587    RUNNING                 345             7                    32                   16   0.3                        8453                                               │
│ trial_1f587    RUNNING                 447             5                    41                   11   0.3                        5629                                               │
│ trial_1f587    RUNNING                 469             7                    52                   23   0.3                        9185                                               │
│ trial_1f587    RUNNING                 314             5                    59                   19   0.3                        1912                                               │
│ trial_1f587    TERMINATED              343             5                    38                   23   0.3                        4593        1            25.5856          0.765752 │
│ trial_1f587    TERMINATED              383             6                    52                   19   sqrt                       8793        1            24.0269          0.784285 │
│ trial_1f587    TERMINATED              364             6                    37                   28   sqrt                       5587        1            22.4998          0.791698 │
│ trial_1f587    TERMINATED              251             5                    25                   19   0.3                        6804        1            22.1202          0.767235 │
│ trial_1f587    TERMINATED              244             5                    49                   20   0.3                        5539        1            22.6004          0.767976 │
│ trial_1f587    TERMINATED              264             6                    50                   18   0.3                        2156        1            24.6461          0.779837 │
│ trial_1f587    TERMINATED              297             6                    50                   24   sqrt                       9411        1            24.0684          0.785767 │
│ trial_1f587    TERMINATED              237             5                    26                   14   0.3                        4625        1            23.8567          0.767976 │
│ trial_1f587    TERMINATED              203             7                    53                   12   0.3                        9522        1            24.1349          0.797628 │
│ trial_1f587    TERMINATED              276             5                    26                   20   sqrt                         52        1            20.9063          0.778354 │
│ trial_1f587    TERMINATED              228             6                    40                   17   0.3                        6817        1            23.8098          0.770941 │
│ trial_1f587    TERMINATED              255             6                    37                   20   sqrt                       7491        1            15.7922          0.774648 │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:28. Total running time: 30s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             27.8657 │
│ time_total_s                 27.8657 │
│ training_iteration                 1 │
│ test_accuracy                0.76872 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:28. Total running time: 30s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:29. Total running time: 31s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             27.8947 │
│ time_total_s                 27.8947 │
│ training_iteration                 1 │
│ test_accuracy                0.76946 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:29. Total running time: 31s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:29. Total running time: 31s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             28.1796 │
│ time_total_s                 28.1796 │
│ training_iteration                 1 │
│ test_accuracy                0.76798 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:29. Total running time: 31s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:30. Total running time: 32s
[36m(train_brf_ray_tune pid=1347156)[0m [Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.1s[32m [repeated 29x across cluster][0m
[36m(train_brf_ray_tune pid=1347154)[0m [Parallel(n_jobs=-1)]: Done 496 out of 496 | elapsed:   24.8s finished[32m [repeated 20x across cluster][0m
2025-11-06 13:43:31,619	INFO tune.py:1009 -- Wrote the latest version of all result files and experiment state to '/mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_PI/case_PI_BRF_acc_superclasses_CPA_METs/BalancedRF_hyperparameters_tuning' in 0.0091s.
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             29.3319 │
│ time_total_s                 29.3319 │
│ training_iteration                 1 │
│ test_accuracy                0.78651 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:30. Total running time: 32s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:30. Total running time: 32s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             29.3463 │
│ time_total_s                 29.3463 │
│ training_iteration                 1 │
│ test_accuracy                0.79096 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:30. Total running time: 32s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:30. Total running time: 32s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             29.5459 │
│ time_total_s                 29.5459 │
│ training_iteration                 1 │
│ test_accuracy                0.78651 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:30. Total running time: 32s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:31. Total running time: 33s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             30.5282 │
│ time_total_s                 30.5282 │
│ training_iteration                 1 │
│ test_accuracy                0.79318 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:31. Total running time: 33s

Trial trial_1f587 finished iteration 1 at 2025-11-06 13:43:31. Total running time: 33s
╭──────────────────────────────────────╮
│ Trial trial_1f587 result             │
├──────────────────────────────────────┤
│ checkpoint_dir_name                  │
│ time_this_iter_s             30.7123 │
│ time_total_s                 30.7123 │
│ training_iteration                 1 │
│ test_accuracy                0.78799 │
╰──────────────────────────────────────╯

Trial trial_1f587 completed after 1 iterations at 2025-11-06 13:43:31. Total running time: 33s

Trial status: 20 TERMINATED
Current time: 2025-11-06 13:43:31. Total running time: 33s
Logical resource usage: 1.0/20 CPUs, 0/1 GPUs (0.0/1.0 accelerator_type:G)
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
╭─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ Trial name     status         n_estimators     max_depth     min_samples_split     min_samples_leaf   max_features       random_state     iter     total time (s)     test_accuracy │
├─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┤
│ trial_1f587    TERMINATED              343             5                    38                   23   0.3                        4593        1            25.5856          0.765752 │
│ trial_1f587    TERMINATED              315             7                    35                   11   0.3                        8746        1            29.3463          0.790956 │
│ trial_1f587    TERMINATED              383             6                    52                   19   sqrt                       8793        1            24.0269          0.784285 │
│ trial_1f587    TERMINATED              364             6                    37                   28   sqrt                       5587        1            22.4998          0.791698 │
│ trial_1f587    TERMINATED              251             5                    25                   19   0.3                        6804        1            22.1202          0.767235 │
│ trial_1f587    TERMINATED              244             5                    49                   20   0.3                        5539        1            22.6004          0.767976 │
│ trial_1f587    TERMINATED              264             6                    50                   18   0.3                        2156        1            24.6461          0.779837 │
│ trial_1f587    TERMINATED              297             6                    50                   24   sqrt                       9411        1            24.0684          0.785767 │
│ trial_1f587    TERMINATED              339             5                    49                   11   0.3                        3702        1            27.8947          0.769459 │
│ trial_1f587    TERMINATED              496             7                    35                   10   0.3                        2487        1            30.5282          0.79318  │
│ trial_1f587    TERMINATED              365             7                    52                   22   0.3                        2153        1            29.5459          0.786509 │
│ trial_1f587    TERMINATED              237             5                    26                   14   0.3                        4625        1            23.8567          0.767976 │
│ trial_1f587    TERMINATED              203             7                    53                   12   0.3                        9522        1            24.1349          0.797628 │
│ trial_1f587    TERMINATED              345             7                    32                   16   0.3                        8453        1            29.3319          0.786509 │
│ trial_1f587    TERMINATED              276             5                    26                   20   sqrt                         52        1            20.9063          0.778354 │
│ trial_1f587    TERMINATED              228             6                    40                   17   0.3                        6817        1            23.8098          0.770941 │
│ trial_1f587    TERMINATED              447             5                    41                   11   0.3                        5629        1            28.1796          0.767976 │
│ trial_1f587    TERMINATED              469             7                    52                   23   0.3                        9185        1            30.7123          0.787991 │
│ trial_1f587    TERMINATED              255             6                    37                   20   sqrt                       7491        1            15.7922          0.774648 │
│ trial_1f587    TERMINATED              314             5                    59                   19   0.3                        1912        1            27.8657          0.768718 │
╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Mejores hiperparámetros: {'n_estimators': 203, 'max_depth': 7, 'min_samples_split': 53, 'min_samples_leaf': 12, 'max_features': 0.3, 'random_state': 9522}
Saved model to disk
[36m(train_brf_ray_tune pid=1347149)[0m [Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.[32m [repeated 16x across cluster][0m
[36m(train_brf_ray_tune pid=1347149)[0m /home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/ray/train/_internal/session.py:772: RayDeprecationWarning: `ray.train.report` should be switched to `ray.tune.report` when running in a function passed to Ray Tune. This will be an error in the future. See this issue for more context: https://github.com/ray-project/ray/issues/49454[32m [repeated 8x across cluster][0m
[36m(train_brf_ray_tune pid=1347149)[0m   _log_deprecation_warning([32m [repeated 8x across cluster][0m
[36m(train_brf_ray_tune pid=1347149)[0m [Parallel(n_jobs=20)]: Done 410 tasks      | elapsed:    0.1s[32m [repeated 13x across cluster][0m
[36m(train_brf_ray_tune pid=1347149)[0m [Parallel(n_jobs=20)]: Done 469 out of 469 | elapsed:    0.1s finished[32m [repeated 5x across cluster][0m
2025-11-06 13:43:42.359769: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:43:42.370894: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433022.383813 1350492 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433022.387926 1350492 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433022.397994 1350492 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433022.398020 1350492 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433022.398022 1350492 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433022.398023 1350492 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:43:42.401178: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.2s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
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Training a non-convolutional model.
Saved model to disk

=== EJECUCIÓN 1 ===

--- TRAIN (ejecución 1) ---

--- TEST (ejecución 1) ---
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 1. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 79.09 [%]
Global accuracy score (test) = 78.72 [%]
Global F1 score (train) = 79.25 [%]
Global F1 score (test) = 79.3 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.63      0.53      0.58       350
MODERATE-INTENSITY       0.62      0.76      0.68       350
         SEDENTARY       0.98      0.97      0.97       350
VIGOROUS-INTENSITY       0.97      0.91      0.94       299

          accuracy                           0.79      1349
         macro avg       0.80      0.79      0.79      1349
      weighted avg       0.79      0.79      0.79      1349


Accuracy capturado en la ejecución 1: 78.72 [%]
F1-score capturado en la ejecución 1: 79.3 [%]

=== EJECUCIÓN 2 ===

--- TRAIN (ejecución 2) ---

--- TEST (ejecución 2) ---
2025-11-06 13:43:55.089497: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:43:55.101027: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433035.114786 1350843 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433035.118955 1350843 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433035.128820 1350843 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433035.128846 1350843 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433035.128848 1350843 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433035.128849 1350843 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:43:55.131960: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 1. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.84 [%]
Global accuracy score (test) = 79.69 [%]
Global F1 score (train) = 78.85 [%]
Global F1 score (test) = 80.07 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.69      0.51      0.59       350
MODERATE-INTENSITY       0.62      0.84      0.71       350
         SEDENTARY       0.98      0.95      0.97       350
VIGOROUS-INTENSITY       0.98      0.90      0.94       299

          accuracy                           0.80      1349
         macro avg       0.82      0.80      0.80      1349
      weighted avg       0.81      0.80      0.80      1349


Accuracy capturado en la ejecución 2: 79.69 [%]
F1-score capturado en la ejecución 2: 80.07 [%]

=== EJECUCIÓN 3 ===

--- TRAIN (ejecución 3) ---

--- TEST (ejecución 3) ---
2025-11-06 13:44:07.821852: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:44:07.832919: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433047.845914 1351159 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433047.849877 1351159 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433047.859655 1351159 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433047.859681 1351159 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433047.859683 1351159 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433047.859684 1351159 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:44:07.862719: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 1. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.12 [%]
Global accuracy score (test) = 78.87 [%]
Global F1 score (train) = 77.87 [%]
Global F1 score (test) = 78.6 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.75      0.40      0.53       350
MODERATE-INTENSITY       0.58      0.91      0.71       350
         SEDENTARY       0.98      0.96      0.97       350
VIGOROUS-INTENSITY       0.98      0.90      0.94       299

          accuracy                           0.79      1349
         macro avg       0.82      0.79      0.79      1349
      weighted avg       0.82      0.79      0.78      1349


Accuracy capturado en la ejecución 3: 78.87 [%]
F1-score capturado en la ejecución 3: 78.6 [%]

=== EJECUCIÓN 4 ===

--- TRAIN (ejecución 4) ---

--- TEST (ejecución 4) ---
2025-11-06 13:44:20.612301: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:44:20.623495: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433060.636428 1351519 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433060.640460 1351519 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433060.650230 1351519 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433060.650248 1351519 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433060.650257 1351519 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433060.650258 1351519 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:44:20.653478: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 0. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 79.74 [%]
Global accuracy score (test) = 79.02 [%]
Global F1 score (train) = 79.96 [%]
Global F1 score (test) = 79.47 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.67      0.54      0.59       350
MODERATE-INTENSITY       0.62      0.77      0.68       350
         SEDENTARY       0.98      0.96      0.97       350
VIGOROUS-INTENSITY       0.95      0.91      0.93       299

          accuracy                           0.79      1349
         macro avg       0.80      0.79      0.79      1349
      weighted avg       0.80      0.79      0.79      1349


Accuracy capturado en la ejecución 4: 79.02 [%]
F1-score capturado en la ejecución 4: 79.47 [%]

=== EJECUCIÓN 5 ===

--- TRAIN (ejecución 5) ---

--- TEST (ejecución 5) ---
2025-11-06 13:44:33.334211: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:44:33.345786: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433073.359042 1351841 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433073.363183 1351841 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433073.373149 1351841 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433073.373171 1351841 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433073.373179 1351841 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433073.373181 1351841 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:44:33.376193: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 1. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 79.28 [%]
Global accuracy score (test) = 78.95 [%]
Global F1 score (train) = 79.48 [%]
Global F1 score (test) = 79.2 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.67      0.48      0.56       350
MODERATE-INTENSITY       0.61      0.81      0.70       350
         SEDENTARY       0.98      0.97      0.97       350
VIGOROUS-INTENSITY       0.96      0.91      0.94       299

          accuracy                           0.79      1349
         macro avg       0.81      0.79      0.79      1349
      weighted avg       0.80      0.79      0.79      1349


Accuracy capturado en la ejecución 5: 78.95 [%]
F1-score capturado en la ejecución 5: 79.2 [%]

=== EJECUCIÓN 6 ===

--- TRAIN (ejecución 6) ---

--- TEST (ejecución 6) ---
2025-11-06 13:44:46.078544: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:44:46.089969: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433086.103169 1352179 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433086.107306 1352179 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433086.117380 1352179 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433086.117400 1352179 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433086.117403 1352179 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433086.117411 1352179 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:44:46.120534: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 0. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 77.48 [%]
Global accuracy score (test) = 79.61 [%]
Global F1 score (train) = 77.43 [%]
Global F1 score (test) = 79.65 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.71      0.47      0.57       350
MODERATE-INTENSITY       0.61      0.86      0.72       350
         SEDENTARY       0.98      0.96      0.97       350
VIGOROUS-INTENSITY       0.95      0.91      0.93       299

          accuracy                           0.80      1349
         macro avg       0.82      0.80      0.80      1349
      weighted avg       0.81      0.80      0.79      1349


Accuracy capturado en la ejecución 6: 79.61 [%]
F1-score capturado en la ejecución 6: 79.65 [%]

=== EJECUCIÓN 7 ===

--- TRAIN (ejecución 7) ---

--- TEST (ejecución 7) ---
2025-11-06 13:44:58.749222: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:44:58.760461: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433098.773483 1352503 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433098.777556 1352503 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433098.787276 1352503 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433098.787295 1352503 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433098.787297 1352503 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433098.787306 1352503 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:44:58.790346: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.2s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 0. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 77.0 [%]
Global accuracy score (test) = 77.61 [%]
Global F1 score (train) = 77.02 [%]
Global F1 score (test) = 77.5 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.68      0.40      0.50       350
MODERATE-INTENSITY       0.57      0.86      0.69       350
         SEDENTARY       0.98      0.95      0.97       350
VIGOROUS-INTENSITY       0.97      0.91      0.94       299

          accuracy                           0.78      1349
         macro avg       0.80      0.78      0.78      1349
      weighted avg       0.80      0.78      0.77      1349


Accuracy capturado en la ejecución 7: 77.61 [%]
F1-score capturado en la ejecución 7: 77.5 [%]

=== EJECUCIÓN 8 ===

--- TRAIN (ejecución 8) ---

--- TEST (ejecución 8) ---
2025-11-06 13:45:11.541082: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:45:11.552261: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433111.565450 1352851 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433111.569669 1352851 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433111.579547 1352851 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433111.579567 1352851 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433111.579569 1352851 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433111.579579 1352851 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:45:11.582727: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 1. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 79.8 [%]
Global accuracy score (test) = 79.84 [%]
Global F1 score (train) = 79.97 [%]
Global F1 score (test) = 80.0 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.70      0.48      0.57       350
MODERATE-INTENSITY       0.62      0.87      0.72       350
         SEDENTARY       0.98      0.96      0.97       350
VIGOROUS-INTENSITY       0.97      0.90      0.94       299

          accuracy                           0.80      1349
         macro avg       0.82      0.80      0.80      1349
      weighted avg       0.81      0.80      0.79      1349


Accuracy capturado en la ejecución 8: 79.84 [%]
F1-score capturado en la ejecución 8: 80.0 [%]

=== EJECUCIÓN 9 ===

--- TRAIN (ejecución 9) ---

--- TEST (ejecución 9) ---
2025-11-06 13:45:24.333056: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:45:24.344760: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433124.358620 1353168 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433124.362835 1353168 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433124.373323 1353168 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433124.373345 1353168 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433124.373347 1353168 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433124.373349 1353168 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:45:24.376523: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 1. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 80.03 [%]
Global accuracy score (test) = 79.91 [%]
Global F1 score (train) = 80.33 [%]
Global F1 score (test) = 80.4 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.68      0.55      0.61       350
MODERATE-INTENSITY       0.63      0.79      0.70       350
         SEDENTARY       0.98      0.96      0.97       350
VIGOROUS-INTENSITY       0.97      0.91      0.94       299

          accuracy                           0.80      1349
         macro avg       0.81      0.80      0.80      1349
      weighted avg       0.81      0.80      0.80      1349


Accuracy capturado en la ejecución 9: 79.91 [%]
F1-score capturado en la ejecución 9: 80.4 [%]

=== EJECUCIÓN 10 ===

--- TRAIN (ejecución 10) ---

--- TEST (ejecución 10) ---
2025-11-06 13:45:37.151450: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:45:37.163006: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433137.176916 1353514 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433137.181054 1353514 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433137.191007 1353514 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433137.191026 1353514 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433137.191028 1353514 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433137.191030 1353514 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:45:37.194166: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 1. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.81 [%]
Global accuracy score (test) = 79.1 [%]
Global F1 score (train) = 78.73 [%]
Global F1 score (test) = 78.85 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.73      0.42      0.54       350
MODERATE-INTENSITY       0.60      0.89      0.72       350
         SEDENTARY       0.98      0.96      0.97       350
VIGOROUS-INTENSITY       0.96      0.90      0.93       299

          accuracy                           0.79      1349
         macro avg       0.82      0.80      0.79      1349
      weighted avg       0.81      0.79      0.78      1349


Accuracy capturado en la ejecución 10: 79.1 [%]
F1-score capturado en la ejecución 10: 78.85 [%]

=== EJECUCIÓN 11 ===

--- TRAIN (ejecución 11) ---

--- TEST (ejecución 11) ---
2025-11-06 13:45:49.925055: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:45:49.936277: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433149.949832 1353829 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433149.953974 1353829 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433149.964220 1353829 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433149.964241 1353829 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433149.964243 1353829 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433149.964245 1353829 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:45:49.967339: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 0. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 79.65 [%]
Global accuracy score (test) = 79.02 [%]
Global F1 score (train) = 79.92 [%]
Global F1 score (test) = 79.65 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.64      0.57      0.60       350
MODERATE-INTENSITY       0.63      0.75      0.69       350
         SEDENTARY       0.98      0.95      0.97       350
VIGOROUS-INTENSITY       0.96      0.90      0.93       299

          accuracy                           0.79      1349
         macro avg       0.80      0.79      0.80      1349
      weighted avg       0.80      0.79      0.79      1349


Accuracy capturado en la ejecución 11: 79.02 [%]
F1-score capturado en la ejecución 11: 79.65 [%]

=== EJECUCIÓN 12 ===

--- TRAIN (ejecución 12) ---

--- TEST (ejecución 12) ---
2025-11-06 13:46:02.710635: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:46:02.721693: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433162.734874 1354168 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433162.738860 1354168 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433162.749014 1354168 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433162.749033 1354168 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433162.749035 1354168 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433162.749037 1354168 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:46:02.752197: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.2s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 1. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.97 [%]
Global accuracy score (test) = 79.32 [%]
Global F1 score (train) = 79.07 [%]
Global F1 score (test) = 79.53 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.69      0.48      0.57       350
MODERATE-INTENSITY       0.61      0.83      0.70       350
         SEDENTARY       0.98      0.97      0.97       350
VIGOROUS-INTENSITY       0.97      0.91      0.94       299

          accuracy                           0.79      1349
         macro avg       0.81      0.80      0.80      1349
      weighted avg       0.81      0.79      0.79      1349


Accuracy capturado en la ejecución 12: 79.32 [%]
F1-score capturado en la ejecución 12: 79.53 [%]

=== EJECUCIÓN 13 ===

--- TRAIN (ejecución 13) ---

--- TEST (ejecución 13) ---
2025-11-06 13:46:15.477060: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:46:15.488397: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433175.501638 1354478 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433175.505721 1354478 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433175.515577 1354478 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433175.515596 1354478 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433175.515598 1354478 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433175.515600 1354478 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:46:15.518766: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 1. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.47 [%]
Global accuracy score (test) = 79.02 [%]
Global F1 score (train) = 78.49 [%]
Global F1 score (test) = 78.78 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.73      0.42      0.53       350
MODERATE-INTENSITY       0.60      0.89      0.71       350
         SEDENTARY       0.98      0.97      0.97       350
VIGOROUS-INTENSITY       0.96      0.90      0.93       299

          accuracy                           0.79      1349
         macro avg       0.82      0.79      0.79      1349
      weighted avg       0.81      0.79      0.78      1349


Accuracy capturado en la ejecución 13: 79.02 [%]
F1-score capturado en la ejecución 13: 78.78 [%]

=== EJECUCIÓN 14 ===

--- TRAIN (ejecución 14) ---

--- TEST (ejecución 14) ---
2025-11-06 13:46:28.184382: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:46:28.195779: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433188.209234 1354814 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433188.213299 1354814 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433188.223142 1354814 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433188.223161 1354814 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433188.223163 1354814 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433188.223164 1354814 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:46:28.226230: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 1. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.33 [%]
Global accuracy score (test) = 78.35 [%]
Global F1 score (train) = 78.44 [%]
Global F1 score (test) = 78.34 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.70      0.43      0.53       350
MODERATE-INTENSITY       0.59      0.86      0.70       350
         SEDENTARY       0.98      0.95      0.96       350
VIGOROUS-INTENSITY       0.96      0.91      0.93       299

          accuracy                           0.78      1349
         macro avg       0.81      0.79      0.78      1349
      weighted avg       0.80      0.78      0.78      1349


Accuracy capturado en la ejecución 14: 78.35 [%]
F1-score capturado en la ejecución 14: 78.34 [%]

=== EJECUCIÓN 15 ===

--- TRAIN (ejecución 15) ---

--- TEST (ejecución 15) ---
2025-11-06 13:46:40.947314: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:46:40.958781: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433200.972173 1355122 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433200.976233 1355122 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433200.986392 1355122 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433200.986413 1355122 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433200.986416 1355122 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433200.986417 1355122 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:46:40.989500: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 1. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.58 [%]
Global accuracy score (test) = 80.28 [%]
Global F1 score (train) = 78.47 [%]
Global F1 score (test) = 80.21 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.76      0.46      0.57       350
MODERATE-INTENSITY       0.61      0.89      0.72       350
         SEDENTARY       0.98      0.97      0.98       350
VIGOROUS-INTENSITY       0.97      0.91      0.94       299

          accuracy                           0.80      1349
         macro avg       0.83      0.81      0.80      1349
      weighted avg       0.82      0.80      0.80      1349


Accuracy capturado en la ejecución 15: 80.28 [%]
F1-score capturado en la ejecución 15: 80.21 [%]

=== EJECUCIÓN 16 ===

--- TRAIN (ejecución 16) ---

--- TEST (ejecución 16) ---
2025-11-06 13:46:53.769643: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:46:53.781266: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433213.794474 1355461 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433213.798418 1355461 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433213.808246 1355461 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433213.808265 1355461 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433213.808268 1355461 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433213.808269 1355461 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:46:53.811352: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 0. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.93 [%]
Global accuracy score (test) = 79.02 [%]
Global F1 score (train) = 79.16 [%]
Global F1 score (test) = 79.45 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.67      0.52      0.59       350
MODERATE-INTENSITY       0.61      0.79      0.69       350
         SEDENTARY       0.98      0.97      0.97       350
VIGOROUS-INTENSITY       0.96      0.90      0.93       299

          accuracy                           0.79      1349
         macro avg       0.80      0.79      0.79      1349
      weighted avg       0.80      0.79      0.79      1349


Accuracy capturado en la ejecución 16: 79.02 [%]
F1-score capturado en la ejecución 16: 79.45 [%]

=== EJECUCIÓN 17 ===

--- TRAIN (ejecución 17) ---

--- TEST (ejecución 17) ---
2025-11-06 13:47:06.614496: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:47:06.625754: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433226.638784 1355799 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433226.642784 1355799 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433226.652831 1355799 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433226.652851 1355799 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433226.652853 1355799 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433226.652855 1355799 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:47:06.656007: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 0. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 80.43 [%]
Global accuracy score (test) = 79.76 [%]
Global F1 score (train) = 80.64 [%]
Global F1 score (test) = 80.1 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.68      0.52      0.59       350
MODERATE-INTENSITY       0.63      0.83      0.71       350
         SEDENTARY       0.98      0.96      0.97       350
VIGOROUS-INTENSITY       0.96      0.91      0.93       299

          accuracy                           0.80      1349
         macro avg       0.81      0.80      0.80      1349
      weighted avg       0.81      0.80      0.80      1349


Accuracy capturado en la ejecución 17: 79.76 [%]
F1-score capturado en la ejecución 17: 80.1 [%]

=== EJECUCIÓN 18 ===

--- TRAIN (ejecución 18) ---

--- TEST (ejecución 18) ---
2025-11-06 13:47:19.323084: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:47:19.334517: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433239.348408 1356114 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433239.352780 1356114 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433239.363429 1356114 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433239.363455 1356114 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433239.363457 1356114 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433239.363459 1356114 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:47:19.366782: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 0. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.02 [%]
Global accuracy score (test) = 77.84 [%]
Global F1 score (train) = 77.83 [%]
Global F1 score (test) = 77.62 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.72      0.40      0.52       350
MODERATE-INTENSITY       0.57      0.86      0.69       350
         SEDENTARY       0.98      0.96      0.97       350
VIGOROUS-INTENSITY       0.95      0.91      0.93       299

          accuracy                           0.78      1349
         macro avg       0.81      0.78      0.78      1349
      weighted avg       0.80      0.78      0.77      1349


Accuracy capturado en la ejecución 18: 77.84 [%]
F1-score capturado en la ejecución 18: 77.62 [%]

=== EJECUCIÓN 19 ===

--- TRAIN (ejecución 19) ---

--- TEST (ejecución 19) ---
2025-11-06 13:47:32.103387: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:47:32.114567: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433252.127728 1356445 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433252.131806 1356445 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433252.141946 1356445 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433252.141965 1356445 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433252.141967 1356445 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433252.141969 1356445 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:47:32.145077: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 1. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 79.56 [%]
Global accuracy score (test) = 80.36 [%]
Global F1 score (train) = 79.8 [%]
Global F1 score (test) = 80.56 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.72      0.50      0.59       350
MODERATE-INTENSITY       0.62      0.83      0.71       350
         SEDENTARY       0.98      0.98      0.98       350
VIGOROUS-INTENSITY       0.97      0.91      0.94       299

          accuracy                           0.80      1349
         macro avg       0.82      0.81      0.81      1349
      weighted avg       0.82      0.80      0.80      1349


Accuracy capturado en la ejecución 19: 80.36 [%]
F1-score capturado en la ejecución 19: 80.56 [%]

=== EJECUCIÓN 20 ===

--- TRAIN (ejecución 20) ---

--- TEST (ejecución 20) ---
2025-11-06 13:47:44.757644: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:47:44.768879: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433264.781998 1356761 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433264.786206 1356761 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433264.796174 1356761 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433264.796193 1356761 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433264.796195 1356761 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433264.796197 1356761 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:47:44.799301: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.2s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 1. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.88 [%]
Global accuracy score (test) = 79.17 [%]
Global F1 score (train) = 78.73 [%]
Global F1 score (test) = 79.19 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.70      0.45      0.55       350
MODERATE-INTENSITY       0.60      0.88      0.72       350
         SEDENTARY       0.98      0.95      0.97       350
VIGOROUS-INTENSITY       0.98      0.90      0.94       299

          accuracy                           0.79      1349
         macro avg       0.82      0.80      0.79      1349
      weighted avg       0.81      0.79      0.79      1349


Accuracy capturado en la ejecución 20: 79.17 [%]
F1-score capturado en la ejecución 20: 79.19 [%]

=== EJECUCIÓN 21 ===

--- TRAIN (ejecución 21) ---

--- TEST (ejecución 21) ---
2025-11-06 13:47:57.534509: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:47:57.545833: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433277.558999 1357097 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433277.563030 1357097 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433277.572812 1357097 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433277.572832 1357097 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433277.572834 1357097 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433277.572836 1357097 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:47:57.575923: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 1. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 79.24 [%]
Global accuracy score (test) = 79.1 [%]
Global F1 score (train) = 79.38 [%]
Global F1 score (test) = 79.43 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.67      0.49      0.57       350
MODERATE-INTENSITY       0.61      0.83      0.71       350
         SEDENTARY       0.98      0.95      0.96       350
VIGOROUS-INTENSITY       0.97      0.91      0.94       299

          accuracy                           0.79      1349
         macro avg       0.81      0.80      0.79      1349
      weighted avg       0.80      0.79      0.79      1349


Accuracy capturado en la ejecución 21: 79.1 [%]
F1-score capturado en la ejecución 21: 79.43 [%]

=== EJECUCIÓN 22 ===

--- TRAIN (ejecución 22) ---

--- TEST (ejecución 22) ---
2025-11-06 13:48:10.390812: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:48:10.402229: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433290.415359 1357404 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433290.419378 1357404 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433290.429401 1357404 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433290.429420 1357404 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433290.429422 1357404 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433290.429423 1357404 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:48:10.432524: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.2s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 1. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 79.48 [%]
Global accuracy score (test) = 79.69 [%]
Global F1 score (train) = 79.64 [%]
Global F1 score (test) = 79.96 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.69      0.51      0.58       350
MODERATE-INTENSITY       0.62      0.83      0.71       350
         SEDENTARY       0.98      0.96      0.97       350
VIGOROUS-INTENSITY       0.96      0.91      0.93       299

          accuracy                           0.80      1349
         macro avg       0.81      0.80      0.80      1349
      weighted avg       0.81      0.80      0.79      1349


Accuracy capturado en la ejecución 22: 79.69 [%]
F1-score capturado en la ejecución 22: 79.96 [%]

=== EJECUCIÓN 23 ===

--- TRAIN (ejecución 23) ---

--- TEST (ejecución 23) ---
2025-11-06 13:48:23.157175: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:48:23.168622: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433303.181646 1357741 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433303.185648 1357741 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433303.195332 1357741 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433303.195352 1357741 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433303.195354 1357741 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433303.195356 1357741 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:48:23.198508: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 0. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.38 [%]
Global accuracy score (test) = 78.95 [%]
Global F1 score (train) = 78.5 [%]
Global F1 score (test) = 79.29 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.67      0.50      0.57       350
MODERATE-INTENSITY       0.61      0.81      0.69       350
         SEDENTARY       0.98      0.96      0.97       350
VIGOROUS-INTENSITY       0.96      0.91      0.93       299

          accuracy                           0.79      1349
         macro avg       0.81      0.79      0.79      1349
      weighted avg       0.80      0.79      0.79      1349


Accuracy capturado en la ejecución 23: 78.95 [%]
F1-score capturado en la ejecución 23: 79.29 [%]

=== EJECUCIÓN 24 ===

--- TRAIN (ejecución 24) ---

--- TEST (ejecución 24) ---
2025-11-06 13:48:36.017272: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:48:36.028561: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433316.041655 1358056 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433316.045834 1358056 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433316.055953 1358056 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433316.055972 1358056 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433316.055974 1358056 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433316.055976 1358056 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:48:36.059017: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.1s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.3s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 1. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.15 [%]
Global accuracy score (test) = 78.95 [%]
Global F1 score (train) = 78.3 [%]
Global F1 score (test) = 79.02 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.70      0.45      0.54       350
MODERATE-INTENSITY       0.59      0.85      0.70       350
         SEDENTARY       0.98      0.97      0.98       350
VIGOROUS-INTENSITY       0.98      0.91      0.94       299

          accuracy                           0.79      1349
         macro avg       0.81      0.79      0.79      1349
      weighted avg       0.81      0.79      0.78      1349


Accuracy capturado en la ejecución 24: 78.95 [%]
F1-score capturado en la ejecución 24: 79.02 [%]

=== EJECUCIÓN 25 ===

--- TRAIN (ejecución 25) ---

--- TEST (ejecución 25) ---
2025-11-06 13:48:48.865042: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:48:48.876305: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433328.889220 1358392 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433328.893289 1358392 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433328.902991 1358392 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433328.903009 1358392 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433328.903011 1358392 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433328.903013 1358392 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:48:48.906009: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.2s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 1. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 79.39 [%]
Global accuracy score (test) = 79.24 [%]
Global F1 score (train) = 79.46 [%]
Global F1 score (test) = 79.47 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.67      0.49      0.57       350
MODERATE-INTENSITY       0.62      0.81      0.70       350
         SEDENTARY       0.98      0.97      0.98       350
VIGOROUS-INTENSITY       0.96      0.91      0.93       299

          accuracy                           0.79      1349
         macro avg       0.81      0.80      0.79      1349
      weighted avg       0.80      0.79      0.79      1349


Accuracy capturado en la ejecución 25: 79.24 [%]
F1-score capturado en la ejecución 25: 79.47 [%]

=== EJECUCIÓN 26 ===

--- TRAIN (ejecución 26) ---

--- TEST (ejecución 26) ---
2025-11-06 13:49:01.555098: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:49:01.566249: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433341.579436 1358700 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433341.583660 1358700 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433341.593354 1358700 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433341.593371 1358700 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433341.593373 1358700 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433341.593374 1358700 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:49:01.596422: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 1. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.26 [%]
Global accuracy score (test) = 77.84 [%]
Global F1 score (train) = 78.03 [%]
Global F1 score (test) = 77.38 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.72      0.37      0.49       350
MODERATE-INTENSITY       0.56      0.87      0.69       350
         SEDENTARY       0.98      0.98      0.98       350
VIGOROUS-INTENSITY       0.97      0.91      0.94       299

          accuracy                           0.78      1349
         macro avg       0.81      0.78      0.77      1349
      weighted avg       0.80      0.78      0.77      1349


Accuracy capturado en la ejecución 26: 77.84 [%]
F1-score capturado en la ejecución 26: 77.38 [%]

=== EJECUCIÓN 27 ===

--- TRAIN (ejecución 27) ---

--- TEST (ejecución 27) ---
2025-11-06 13:49:14.223506: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:49:14.234646: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433354.247559 1359037 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433354.251650 1359037 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433354.261471 1359037 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433354.261494 1359037 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433354.261497 1359037 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433354.261499 1359037 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:49:14.264459: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.2s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    0.9s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 1. 1. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 79.27 [%]
Global accuracy score (test) = 78.65 [%]
Global F1 score (train) = 79.45 [%]
Global F1 score (test) = 79.15 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.65      0.51      0.57       350
MODERATE-INTENSITY       0.60      0.78      0.68       350
         SEDENTARY       0.98      0.97      0.97       350
VIGOROUS-INTENSITY       0.97      0.91      0.94       299

          accuracy                           0.79      1349
         macro avg       0.80      0.79      0.79      1349
      weighted avg       0.80      0.79      0.79      1349


Accuracy capturado en la ejecución 27: 78.65 [%]
F1-score capturado en la ejecución 27: 79.15 [%]

=== EJECUCIÓN 28 ===

--- TRAIN (ejecución 28) ---

--- TEST (ejecución 28) ---
2025-11-06 13:49:26.867746: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:49:26.878896: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433366.892554 1359359 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433366.896495 1359359 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433366.906998 1359359 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433366.907017 1359359 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433366.907020 1359359 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433366.907021 1359359 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:49:26.910127: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.1s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    1.0s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.3s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
This activity can't be balanced (in a downsampling way)
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This activity can't be balanced (in a downsampling way)
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[1. 0. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.11 [%]
Global accuracy score (test) = 77.54 [%]
Global F1 score (train) = 78.13 [%]
Global F1 score (test) = 77.33 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.69      0.39      0.50       350
MODERATE-INTENSITY       0.57      0.86      0.69       350
         SEDENTARY       0.98      0.96      0.97       350
VIGOROUS-INTENSITY       0.96      0.91      0.94       299

          accuracy                           0.78      1349
         macro avg       0.80      0.78      0.77      1349
      weighted avg       0.80      0.78      0.77      1349


Accuracy capturado en la ejecución 28: 77.54 [%]
F1-score capturado en la ejecución 28: 77.33 [%]

=== EJECUCIÓN 29 ===

--- TRAIN (ejecución 29) ---

--- TEST (ejecución 29) ---
2025-11-06 13:49:39.622783: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2025-11-06 13:49:39.633894: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1762433379.646960 1359696 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1762433379.650974 1359696 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1762433379.660898 1359696 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433379.660916 1359696 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433379.660918 1359696 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1762433379.660919 1359696 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
2025-11-06 13:49:39.664092: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/home/simur/git/uniovi-simur-wearablepermed-ml/.venv/lib/python3.12/site-packages/sklearn/base.py:1389: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().
  return fit_method(estimator, *args, **kwargs)
[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=-1)]: Done  10 tasks      | elapsed:    0.2s
[Parallel(n_jobs=-1)]: Done 160 tasks      | elapsed:    0.9s
[Parallel(n_jobs=-1)]: Done 203 out of 203 | elapsed:    1.2s finished
[Parallel(n_jobs=20)]: Using backend ThreadingBackend with 20 concurrent workers.
[Parallel(n_jobs=20)]: Done  10 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 160 tasks      | elapsed:    0.0s
[Parallel(n_jobs=20)]: Done 203 out of 203 | elapsed:    0.0s finished
1 GPU(s) detected and VRAM set to crossover mode..
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Training a non-convolutional model.
Saved model to disk
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 0. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 79.7 [%]
Global accuracy score (test) = 79.47 [%]
Global F1 score (train) = 79.94 [%]
Global F1 score (test) = 79.82 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.67      0.51      0.58       350
MODERATE-INTENSITY       0.62      0.80      0.70       350
         SEDENTARY       0.98      0.97      0.97       350
VIGOROUS-INTENSITY       0.96      0.91      0.94       299

          accuracy                           0.79      1349
         macro avg       0.81      0.80      0.80      1349
      weighted avg       0.80      0.79      0.79      1349


Accuracy capturado en la ejecución 29: 79.47 [%]
F1-score capturado en la ejecución 29: 79.82 [%]

=== EJECUCIÓN 30 ===

--- TRAIN (ejecución 30) ---

--- TEST (ejecución 30) ---
['LIGHT-INTENSITY' 'MODERATE-INTENSITY' 'SEDENTARY' 'VIGOROUS-INTENSITY']
4
Mapeo de etiquetas: {'LIGHT-INTENSITY': 0, 'MODERATE-INTENSITY': 1, 'SEDENTARY': 2, 'VIGOROUS-INTENSITY': 3}
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This activity can't be balanced (in a downsampling way)
Training a non-convolutional model.
Loaded model from disk
(1349, 42)
(12556, 42)
[[0.]
 [0.]
 [0.]
 ...
 [3.]
 [3.]
 [3.]]
(1349, 1)
[0. 0. 0. ... 3. 3. 2.]
(1349,)
-------------------------------------------------

Global accuracy score (train) = 78.43 [%]
Global accuracy score (test) = 79.17 [%]
Global F1 score (train) = 78.54 [%]
Global F1 score (test) = 79.31 [%]
                    precision    recall  f1-score   support

   LIGHT-INTENSITY       0.69      0.47      0.56       350
MODERATE-INTENSITY       0.61      0.83      0.70       350
         SEDENTARY       0.98      0.97      0.97       350
VIGOROUS-INTENSITY       0.96      0.91      0.94       299

          accuracy                           0.79      1349
         macro avg       0.81      0.80      0.79      1349
      weighted avg       0.80      0.79      0.79      1349


Accuracy capturado en la ejecución 30: 79.17 [%]
F1-score capturado en la ejecución 30: 79.31 [%]

=== RESUMEN FINAL ===
Accuracies: [78.72, 79.69, 78.87, 79.02, 78.95, 79.61, 77.61, 79.84, 79.91, 79.1, 79.02, 79.32, 79.02, 78.35, 80.28, 79.02, 79.76, 77.84, 80.36, 79.17, 79.1, 79.69, 78.95, 78.95, 79.24, 77.84, 78.65, 77.54, 79.47, 79.17]
F1-scores: [79.3, 80.07, 78.6, 79.47, 79.2, 79.65, 77.5, 80.0, 80.4, 78.85, 79.65, 79.53, 78.78, 78.34, 80.21, 79.45, 80.1, 77.62, 80.56, 79.19, 79.43, 79.96, 79.29, 79.02, 79.47, 77.38, 79.15, 77.33, 79.82, 79.31]
Accuracy mean: 79.0687 | std: 0.6987
F1 mean: 79.2210 | std: 0.8544

Resultados guardados en /mnt/nvme1n2/git/uniovi-simur-wearablepermed-data/output/Paper_results/cases_dataset_PI/case_PI_BRF_acc_superclasses_CPA_METs/metrics_test.npz
