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results_inception_time_city_2nd_rnd.txt
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nohup: ignoring input
/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/torch/cuda/__init__.py:141: UserWarning: CUDA initialization: The NVIDIA driver on your system is too old (found version 11020). Please update your GPU driver by downloading and installing a new version from the URL: http://www.nvidia.com/Download/index.aspx Alternatively, go to: https://pytorch.org to install a PyTorch version that has been compiled with your version of the CUDA driver. (Triggered internally at ../c10/cuda/CUDAFunctions.cpp:108.)
return torch._C._cuda_getDeviceCount() > 0
2024-11-29 07:02:51.858479: 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 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-11-29 07:02:53.899459: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
2024-11-29 07:02:54.932216: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:998] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
2024-11-29 07:02:54.934354: W tensorflow/core/common_runtime/gpu/gpu_device.cc:2251] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
GPU is not available
Start time: 2024-29-11_07-02-50
timeseries_0_0_f1-5 (871, 24) (871,) (218, 24) (218,)
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_0_f1-5 {'accuracy_score': 0.2889908256880734, 'f1_score': 0.2249313452267133, 'precision_score': 0.46279225927543965, 'recall_score': 0.2889908256880734}
timeseries_0_0_f2-5 (871, 24) (871,) (218, 24) (218,)
Loaded: timeseries_0_0_f2-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
WARNING:tensorflow:5 out of the last 9 calls to <function TensorFlowTrainer.make_predict_function.<locals>.one_step_on_data_distributed at 0x7f72ad626c10> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.
<function run_inception_time at 0x7f72adcfce50>_0_0_f2-5 {'accuracy_score': 0.37155963302752293, 'f1_score': 0.27846840072167384, 'precision_score': 0.7177822415707357, 'recall_score': 0.37155963302752293}
timeseries_0_0_f3-5 (871, 24) (871,) (218, 24) (218,)
Loaded: timeseries_0_0_f3-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_0_f3-5 {'accuracy_score': 0.22018348623853212, 'f1_score': 0.09707330582690295, 'precision_score': 0.4276080433904564, 'recall_score': 0.22018348623853212}
timeseries_0_0_f4-5 (871, 24) (871,) (218, 24) (218,)
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_0_f4-5 {'accuracy_score': 0.43577981651376146, 'f1_score': 0.39553966185935135, 'precision_score': 0.45353192471049625, 'recall_score': 0.43577981651376146}
timeseries_0_0_f5-5 (872, 24) (872,) (217, 24) (217,)
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_0_f5-5 {'accuracy_score': 0.14746543778801843, 'f1_score': 0.03820966809082259, 'precision_score': 0.02194834422891437, 'recall_score': 0.14746543778801843}
<function run_inception_time at 0x7f72adcfce50>_0_0
accuracy_score mean=0.2927958 std=0.1030108 t_interval=(0.006792046389800577, 0.5787996333125628)
f1_score mean=0.2068445 std=0.1277109 t_interval=(-0.14773789845895688, 0.5614268511491425)
precision_score mean=0.4167326 std=0.2236423 t_interval=(-0.20419808265263728, 1.037663207923054)
recall_score mean=0.2927958 std=0.1030108 t_interval=(0.006792046389800577, 0.5787996333125628)
timeseries_0_1_f1-5 (1059, 24) (1059,) (265, 24) (265,)
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_1_f1-5 {'accuracy_score': 0.12075471698113208, 'f1_score': 0.03894682909004116, 'precision_score': 0.4256254097763532, 'recall_score': 0.12075471698113208}
timeseries_0_1_f2-5 (1059, 24) (1059,) (265, 24) (265,)
Loaded: timeseries_0_1_f2-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_1_f2-5 {'accuracy_score': 0.08679245283018867, 'f1_score': 0.013910985471040695, 'precision_score': 0.007561463693539165, 'recall_score': 0.08679245283018867}
timeseries_0_1_f3-5 (1059, 24) (1059,) (265, 24) (265,)
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_1_f3-5 {'accuracy_score': 0.30566037735849055, 'f1_score': 0.16034287833725985, 'precision_score': 0.16150272163780716, 'recall_score': 0.30566037735849055}
timeseries_0_1_f4-5 (1059, 24) (1059,) (265, 24) (265,)
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_1_f4-5 {'accuracy_score': 0.09811320754716982, 'f1_score': 0.017964390114270527, 'precision_score': 0.009887377504753546, 'recall_score': 0.09811320754716982}
timeseries_0_1_f5-5 (1060, 24) (1060,) (264, 24) (264,)
Loaded: timeseries_0_1_f5-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_1_f5-5 {'accuracy_score': 0.07196969696969698, 'f1_score': 0.016763783625953713, 'precision_score': 0.2928613053613054, 'recall_score': 0.07196969696969698}
<function run_inception_time at 0x7f72adcfce50>_0_1
accuracy_score mean=0.1366581 std=0.0859902 t_interval=(-0.10208896615485732, 0.3754051468295285)
f1_score mean=0.0495858 std=0.0560896 t_interval=(-0.10614388579442186, 0.20531543244984823)
precision_score mean=0.1794877 std=0.1625323 t_interval=(-0.2717742906855223, 0.6307496018750257)
recall_score mean=0.1366581 std=0.0859902 t_interval=(-0.10208896615485732, 0.3754051468295285)
timeseries_0_2_f1-5 (1658, 24) (1658,) (415, 24) (415,)
Loaded: timeseries_0_2_f1-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_2_f1-5 {'accuracy_score': 0.41204819277108434, 'f1_score': 0.32756067967341235, 'precision_score': 0.45903921809687737, 'recall_score': 0.41204819277108434}
timeseries_0_2_f2-5 (1658, 24) (1658,) (415, 24) (415,)
Loaded: timeseries_0_2_f2-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_2_f2-5 {'accuracy_score': 0.22650602409638554, 'f1_score': 0.17002061090706827, 'precision_score': 0.27684477174897876, 'recall_score': 0.22650602409638554}
timeseries_0_2_f3-5 (1658, 24) (1658,) (415, 24) (415,)
Loaded: timeseries_0_2_f3-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_2_f3-5 {'accuracy_score': 0.38795180722891565, 'f1_score': 0.23839185004777605, 'precision_score': 0.49556056739272364, 'recall_score': 0.38795180722891565}
timeseries_0_2_f4-5 (1659, 24) (1659,) (414, 24) (414,)
Loaded: timeseries_0_2_f4-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_2_f4-5 {'accuracy_score': 0.4613526570048309, 'f1_score': 0.4307904811115028, 'precision_score': 0.4421355724254275, 'recall_score': 0.4613526570048309}
timeseries_0_2_f5-5 (1659, 24) (1659,) (414, 24) (414,)
Loaded: timeseries_0_2_f5-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_0_2_f5-5 {'accuracy_score': 0.17632850241545894, 'f1_score': 0.20103664210671096, 'precision_score': 0.600470415909635, 'recall_score': 0.17632850241545894}
<function run_inception_time at 0x7f72adcfce50>_0_2
accuracy_score mean=0.3328374 std=0.1110221 t_interval=(0.02459071575091798, 0.6410841576557521)
f1_score mean=0.2735601 std=0.0947147 t_interval=(0.010589984533408092, 0.53653012100518)
precision_score mean=0.4548101 std=0.1046209 t_interval=(0.16433578597212695, 0.7452844322573299)
recall_score mean=0.3328374 std=0.1110221 t_interval=(0.02459071575091798, 0.6410841576557521)
timeseries_1_0_f1-5 (2137, 24) (2137,) (535, 24) (535,)
Loaded: timeseries_1_0_f1-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_0_f1-5 {'accuracy_score': 0.30654205607476637, 'f1_score': 0.2235976197534438, 'precision_score': 0.1772776336178689, 'recall_score': 0.30654205607476637}
timeseries_1_0_f2-5 (2137, 24) (2137,) (535, 24) (535,)
Loaded: timeseries_1_0_f2-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_0_f2-5 {'accuracy_score': 0.23738317757009345, 'f1_score': 0.09736588644576222, 'precision_score': 0.15305822057493484, 'recall_score': 0.23738317757009345}
timeseries_1_0_f3-5 (2138, 24) (2138,) (534, 24) (534,)
Loaded: timeseries_1_0_f3-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_0_f3-5 {'accuracy_score': 0.3895131086142322, 'f1_score': 0.2877525876988451, 'precision_score': 0.3951961724673426, 'recall_score': 0.3895131086142322}
timeseries_1_0_f4-5 (2138, 24) (2138,) (534, 24) (534,)
Loaded: timeseries_1_0_f4-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_0_f4-5 {'accuracy_score': 0.028089887640449437, 'f1_score': 0.018504458429656066, 'precision_score': 0.24405481631645662, 'recall_score': 0.028089887640449437}
timeseries_1_0_f5-5 (2138, 24) (2138,) (534, 24) (534,)
Loaded: timeseries_1_0_f5-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_0_f5-5 {'accuracy_score': 0.14232209737827714, 'f1_score': 0.08842089068538653, 'precision_score': 0.2562357035364532, 'recall_score': 0.14232209737827714}
<function run_inception_time at 0x7f72adcfce50>_1_0
accuracy_score mean=0.2207701 std=0.1260054 t_interval=(-0.12907695541986672, 0.5706170863309941)
f1_score mean=0.1431283 std=0.0979895 t_interval=(-0.1289341407217762, 0.4151907179270137)
precision_score mean=0.2451645 std=0.0845287 t_interval=(0.010475235593598087, 0.47985378301162435)
recall_score mean=0.2207701 std=0.1260054 t_interval=(-0.12907695541986672, 0.5706170863309941)
timeseries_1_2_f1-5 (2580, 24) (2580,) (646, 24) (646,)
Loaded: timeseries_1_2_f1-5
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<function run_inception_time at 0x7f72adcfce50>_1_2_f1-5 {'accuracy_score': 0.2647058823529412, 'f1_score': 0.18529541584146683, 'precision_score': 0.4261455349575951, 'recall_score': 0.2647058823529412}
timeseries_1_2_f2-5 (2581, 24) (2581,) (645, 24) (645,)
Loaded: timeseries_1_2_f2-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_2_f2-5 {'accuracy_score': 0.12713178294573643, 'f1_score': 0.12764140439192095, 'precision_score': 0.19821431983072788, 'recall_score': 0.12713178294573643}
timeseries_1_2_f3-5 (2581, 24) (2581,) (645, 24) (645,)
Loaded: timeseries_1_2_f3-5
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<function run_inception_time at 0x7f72adcfce50>_1_2_f3-5 {'accuracy_score': 0.08217054263565891, 'f1_score': 0.05866294935144101, 'precision_score': 0.36946505711826205, 'recall_score': 0.08217054263565891}
timeseries_1_2_f4-5 (2581, 24) (2581,) (645, 24) (645,)
Loaded: timeseries_1_2_f4-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_2_f4-5 {'accuracy_score': 0.023255813953488372, 'f1_score': 0.0010651517841292384, 'precision_score': 0.0005450581395348837, 'recall_score': 0.023255813953488372}
timeseries_1_2_f5-5 (2581, 24) (2581,) (645, 24) (645,)
Loaded: timeseries_1_2_f5-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_2_f5-5 {'accuracy_score': 0.17519379844961241, 'f1_score': 0.06450192891436587, 'precision_score': 0.039527472690352325, 'recall_score': 0.17519379844961241}
<function run_inception_time at 0x7f72adcfce50>_1_2
accuracy_score mean=0.1344916 std=0.0821918 t_interval=(-0.09370955266292447, 0.3626926807978994)
f1_score mean=0.0874334 std=0.0632562 t_interval=(-0.08819394881552213, 0.2630606889288517)
precision_score mean=0.2067795 std=0.1703921 t_interval=(-0.26630475345438614, 0.679863730548975)
recall_score mean=0.1344916 std=0.0821918 t_interval=(-0.09370955266292447, 0.3626926807978994)
timeseries_1_4_f1-5 (1856, 24) (1856,) (464, 24) (464,)
Loaded: timeseries_1_4_f1-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_4_f1-5 {'accuracy_score': 0.3426724137931034, 'f1_score': 0.256998616208506, 'precision_score': 0.3947783088850074, 'recall_score': 0.3426724137931034}
timeseries_1_4_f2-5 (1856, 24) (1856,) (464, 24) (464,)
Loaded: timeseries_1_4_f2-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_4_f2-5 {'accuracy_score': 0.1724137931034483, 'f1_score': 0.054992882733030525, 'precision_score': 0.046921585604577626, 'recall_score': 0.1724137931034483}
timeseries_1_4_f3-5 (1856, 24) (1856,) (464, 24) (464,)
Loaded: timeseries_1_4_f3-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_4_f3-5 {'accuracy_score': 0.2025862068965517, 'f1_score': 0.07746653020003075, 'precision_score': 0.7262136285436457, 'recall_score': 0.2025862068965517}
timeseries_1_4_f4-5 (1856, 24) (1856,) (464, 24) (464,)
Loaded: timeseries_1_4_f4-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_4_f4-5 {'accuracy_score': 0.3599137931034483, 'f1_score': 0.2974070459895591, 'precision_score': 0.44602446509454063, 'recall_score': 0.3599137931034483}
timeseries_1_4_f5-5 (1856, 24) (1856,) (464, 24) (464,)
Loaded: timeseries_1_4_f5-5
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/home/carolina/Documents/Mestrado/.venv/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1344: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
_warn_prf(average, modifier, msg_start, len(result))
<function run_inception_time at 0x7f72adcfce50>_1_4_f5-5 {'accuracy_score': 0.3448275862068966, 'f1_score': 0.17740325978489854, 'precision_score': 0.11942080907598149, 'recall_score': 0.3448275862068966}
<function run_inception_time at 0x7f72adcfce50>_1_4
accuracy_score mean=0.2844828 std=0.0799798 t_interval=(0.06242312565393093, 0.5065423915874483)
f1_score mean=0.1728537 std=0.0955034 t_interval=(-0.09230624781929042, 0.4380135817857004)
precision_score mean=0.3466718 std=0.2440207 t_interval=(-0.3308381839680884, 1.0241817028495896)
recall_score mean=0.2844828 std=0.0799798 t_interval=(0.06242312565393093, 0.5065423915874483)
Classifier mean accuracy_score=0.2336726
Classifier mean f1_score=0.1555676
Classifier mean precision_score=0.3082743
Classifier mean recall_score=0.2336726
End time: 2024-29-11_16-35-39
Running time: 9:32:49.014971
Done!
48597.26user 2334.27system 9:33:02elapsed 148%CPU (0avgtext+0avgdata 1874992maxresident)k
939672inputs+592outputs (46623major+178407984minor)pagefaults 0swaps