{"categories":[{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/6"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/13"},{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics/2"}],"enrichment":{"capability":"OptBinning discretizes numeric variables into bins optimally for binary, continuous, and multiclass targets using mathematical programming, with support for constraints.","skillfed_tags":["feature-engineering","discretization","optimization"],"use_cases":["Feature engineering in credit risk or classification models where binned variables improve interpretability and model performance.","Discretizing continuous predictors in logistic regression or tree-based models with explicit constraints on bin counts or monotonicity.","Exploratory data analysis to find natural or optimal breakpoints in a variable's relationship to a target outcome.","Preprocessing for regulatory or compliance requirements that demand human-interpretable variable bins with documented thresholds."],"what_it_does":"OptBinning is a Python library that solves the optimal binning problem\u2014finding the best way to discretize a continuous or discrete numeric variable into bins to maximize predictive power or meet other objectives with respect to a target variable. It uses rigorous mathematical programming to handle binary, continuous, and multiclass targets, and incorporates constraints that go beyond simpler binning approaches.\n\nThe library depends on numpy, scipy, scikit-learn, pandas, matplotlib, ortools, and ropwr. It is designed for data scientists and researchers working on feature engineering, model preprocessing, and statistical analysis where controlled discretization of variables is needed.","worth_installing":"Yes, if you need principled optimal binning with constraint support for feature engineering. The low install friction, permissive license, and active (though aging) maintenance make it a solid choice. However, verify that its mathematical programming approach and dependency footprint fit your performance and deployment constraints before committing to production use."},"id":"optbinning","links":{"html":"https://skillfed.io/packages/optbinning","md":"https://skillfed.io/packages/optbinning.md","pypi":"https://pypi.org/project/optbinning/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-10-26","license_spdx":null,"license_treatment":"permissive","name":"optbinning","python_support":"supports_current","summary":"OptBinning: The Python Optimal Binning library"},"popularity":{"monthly_downloads":298804,"position":7868,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.21.0"}