imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

Machine Learning & Data Science

interpretability
machine-learning
data-science
artificial-intelligence
ml
ai
statistics
scikit-learn
python
optimal-classification-tree
rulefit
imodels
rule-learning
supervised-learning
explainable-ml

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Stars: 1,626
Forks: 144
+ today: +1
Created: 7y

Ranking data as of October 7, 2026 (UTC).

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1,626 stars

Overview

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible). It ranks #2161 on GitTiger, gaining +1 star on October 7, 2026 (UTC).

The project is written in Jupyter Notebook and has 144 forks. It was created 7y ago.

Installation

git clone https://github.com/csinva/imodels.git
cd imodels
# see README for setup