dpsn's Introduction
Environment python = 3.5 sklearn = 0.22.2.post1 pyts = 0.7.0 Full result .\results\result.txt visulization result of full result .\time_series_proto\image_result\!A.pdf Full interpretability result .\SFA_Python-master\test\image_result How to run Get basline and feature extraction go to folder "~/DPSN/SFA_Python-master/test" using jupyter notebook run from 1_* to 4_* which are: 1_get_SFA_hyper_parameter.ipynb 2_split_dataset_and_prepare_SFA_feature_for_small_dataset.ipynb 3_get_ST_hyper_parameter.ipynb 4_get_ST_result.ipynb DPSN Classification go to folder "~/DPSN/time_series_proto" using terminal to run bash scripts/train_proto.sh 0 2 linear_transform ./exp/train.py ## if you want more dataset change that "name_list" in ./exp/train.py DPSN inter go to folder "~/DPSN/time_series_proto/exp/" using terminal to run bash test_load-shapelet.sh ## if you want more dataset change that "name_list" in ./exp/test_load_model_shapelet.py go to folder "~/DPSN/SFA_Python-master/test" using jupyter notebook to run 5_interpretable_shapelet.ipynb
dpsn's People
dpsn's Issues
'n_bins' must be greater than or equal to 2 and lower than or equal to min(n_samples, 26) (got 67)
While trying to run 2_split_dataset_and_prepare_SFA_feature_for_small_dataset.ipynb, got this error at line BOSS_model.fit(X_train, y_train) at lind 138 of the last cell.
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