PIP: Pictorial Interpretable Prototype Learning for Time Series Classification

The implimentation of PIP: Pictorial Interpretable Prototype Learning for Time Series Classification

Data

We select three datasets: UCI-HAR, UCR-FordA, and UEA-SpokenArabicDigits for our expriment.

Requirments

All python packages needed are listed in requirments.txt file and can be installed as follow:

conda config --append channels conda-forge
conda create --name <your env name> --file requirements.txt

Expriments

To run each expriment you can following commands

python exp/uci-har-exp.py
python exp/ucr-fordA-exp.py
python exp/uea-arabic-exp.py

the result of all expriments save in 'trainin_history' folder.