TSInterpret: A Python Package for the Interpretability of Time Series Classification

Abstract

TSInterpret is a python package that enables post-hoc interpretability and explanation of black-box time series classifiers with three lines of code. Due to the specific structure of time series (i.e., non-independent features (Ismail et al., 2020)) and unintuitive visualizations (Siddiqui et al., 2019), traditional interpretability and explainability libraries like Captum (Kokhlikyan et al., 2020), Alibi Explain (Klaise et al., 2021, or tf-explain (Meudec, 2021) find limited usage. TSInterpret specifically addresses the issue of black-box time series classification by providing a unified interface to state-of-the-art interpretation algorithms in combination with default plots. In addition, the package provides a framework for developing additional easy-to-use interpretability methods.