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