imodels: a python package for fitting interpretable models

Abstract

imodels is a Python package for concise, transparent, and accurate predictive modeling. It provides users a simple interface for fitting and using state-of-the-art interpretable models, all compatible with scikit-learn (Pedregosa et al., 2011). These models can often replace black-box models while improving interpretability and computational efficiency, all without sacrificing predictive accuracy. In addition, the package provides a framework for developing custom tools and rule-based models for interpretability.