Litcius/Paper detail

imodels: a python package for fitting interpretable models

Chandan Singh, Keyan Nasseri, Yan Tan, Tiffany M. Tang, Bin Yu

2021The Journal of Open Source Software24 citationsDOIOpen Access PDF

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 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.

Topics & Concepts

Python (programming language)Computer scienceProgramming languageR packageArtificial intelligenceExplainable Artificial Intelligence (XAI)Reservoir Engineering and Simulation MethodsMachine Learning and Data Classification