PySS3: A Python package implementing a novel text classifier with visualization tools for Explainable AI
This work provides an accessible tool for researchers and practitioners to use a state-of-the-art, explainable text classifier, though it is incremental as it focuses on implementation rather than new algorithmic advances.
The authors tackled the lack of an open-source implementation for the SS3 text classifier by introducing PySS3, a Python package that implements SS3 and includes visualization tools for explainable AI, enabling researchers to deploy robust and interpretable models for text classification.
A recently introduced text classifier, called SS3, has obtained state-of-the-art performance on the CLEF's eRisk tasks. SS3 was created to deal with risk detection over text streams and, therefore, not only supports incremental training and classification but also can visually explain its rationale. However, little attention has been paid to the potential use of SS3 as a general classifier. We believe this could be due to the unavailability of an open-source implementation of SS3. In this work, we introduce PySS3, a package that implements SS3 and also comes with visualization tools that allow researchers to deploy robust, explainable, and trusty machine learning models for text classification.