Catboost Python Packages

catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

skforecast

Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models

catboost-dev

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

mljar-supervised

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

treecf

Constrained, threshold-aware counterfactual explanations for tree ensembles (XGBoost, LightGBM, CatBoost, sklearn) on a bundled Rust engine

hgboost

hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating the results on an independent validation set. hgboost can be applied for classification and regression tasks.

stabilization-uplift

Stabilization of classification ML-models using synthetic data with outliers on Open Data. Metrics on PyPI: pip install stabilization-uplift. NeurIPS 2025 GenAI in Finance Workshop.

boost-loss

Utilities for easy use of custom losses in CatBoost, LightGBM, XGBoost.

pandasflow

A set of custom python modules for friendly workflow on pandas

sklearn-utilities

Utilities for scikit-learn. Append prediction to x, append prediction to x single, append x prediction to x, compose var estimator, data frame wrapper, drop by noise prediction, drop missing rows y, dummy regressor var, estimator wrapper base, excluded column transformer pandas, feature union pandas, id transformer, included column transformer pand

insurance-causal

Causal inference for insurance pricing — DML, CatBoost nuisance models, confounding bias reports

retrofit

Simple, opinionated machine learning workflows for rapid iteration.

hyperparameter-hunter

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

hypergbm

A full pipeline AutoML tool for tabular data

insurance-severity

Severity modelling for insurance pricing - spliced distributions, DRN, composite regression, EQRN extreme quantiles

insurance-quantile

Actuarial tail risk quantile/expectile regression for insurance pricing - TVaR, large loss loading, ILF curves, CatBoost

insurance-demand

Deprecated — merged into insurance-optimise

py-automl-lib

Python package for automated hyperparameter-optimization of common machine-learning algorithms

insurance-distributional

Distributional GBM for insurance pricing — TweedieGBM, GammaGBM, ZIPGBM, NegBinomialGBM, per-risk volatility scoring

insurance-interactions

Automated GLM interaction detection for insurance pricing — CANN, NID scoring, SHAP interaction values

insurance-deploy

Champion/challenger pricing framework — shadow mode, SHA-256 routing, SQLite quote log, bootstrap LR test, ENBP audit (146 tests)

ordinalgbt

A package to build Gradient boosted trees for ordinal labels

insurance-cv

Temporal cross-validation for insurance pricing - respects policy time structure, CatBoost, Polars

insurance-distill

GBM-to-GLM distillation for insurance pricing - surrogate factor tables for Radar/Emblem rating engines