{"repo":"csinva/imodels","free":true,"listed":false,"github":"https://github.com/csinva/imodels","clone":"git clone https://github.com/csinva/imodels.git","description":"Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).","language":"Jupyter Notebook","stars":1615,"topics":["interpretability","machine-learning","data-science","artificial-intelligence","ml","ai","statistics","scikit-learn","python","optimal-classification-tree"],"license":"MIT","category":"machine-learning","readme_excerpt":"Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. Check out our new packages! Interpretability in text: imodelsX , interpretability tools for tabular data with agents: agentic-imodels 📚 docs • 📖 demo notebooks =2.0-blue\" Modern machine-learning models are increasingly complex, often making them difficult to interpret. This package provides 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 (e.g. random forests) with simpler models (e.g. rule lists) while improving interpretability and computational efficiency, all without sacrificing predictive accuracy! Simply import a classifier or regressor and use the fit and predict methods, same as standard scikit-learn models. Installation Install with pip install imodels (see here for help). Supported models 🗂️ Docs   📄 Research paper   🔗 Reference code implementation Model Reference Description :-------------------------- ------------------------------------------------------------ ------------------------------------------------------------ Rulefit rule set 🗂️, 📄, 🔗 Fits a sparse linear model on rules extracted from decision trees Skope rule set 🗂️, 🔗 Extracts rules from gradient-boosted trees, deduplicates them, then linearly combines them based on their OOB precision Boosted rule set 🗂️, 📄, 🔗 Sequentially fits a set of rules with Adabo","default_branch":null,"files":null,"tree":[],"storefront":"/r/csinva","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/csinva/imodels/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}