Scikit-learn alternatives

The best alternatives to Scikit-learn are XGBoost, LightGBM, CatBoost and Statsmodels. Each is an AI tool with a distinct edge — pricing, output quality, or workflow — detailed below and reviewed on Stork.

• XGBoost

  It is an optimized distributed gradient boosting library designed for speed and performance, particularly effective for structured data.

• LightGBM

  Developed by Microsoft, it is a gradient boosting framework that uses tree-based learning algorithms, optimized for speed and efficiency with large datasets.

• CatBoost

  Developed by Yandex, it is a gradient boosting library that excels at handling categorical features automatically without requiring extensive preprocessing.

• Statsmodels

  It is a Python library that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests and statistical data exploration.