DPSN

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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