Gbdt Python Packages

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

lightgbm

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

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.

xgboost-cpu

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

xgboost-cu12

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

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.

mojolearn

GPU machine learning in Mojo that supports bitwise identical inference and training on Apple Metal, NVIDIA CUDA and AMD HIP.

mojolearn-nvidia

GPU machine learning in Mojo that supports bitwise identical inference and training on Apple Metal, NVIDIA CUDA and AMD HIP.

mojolearn-amd

GPU machine learning in Mojo that supports bitwise identical inference and training on Apple Metal, NVIDIA CUDA and AMD HIP.

xgboost-cu13

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

ktboost

A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and loss functions.

chefboost

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python

boost-loss

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

unifiedbooster

Unified interface for Gradient Boosted Decision Trees

pkboost

PKBoost: Adaptive GBDT for Concept Drift, Built from scratch in Rust, PKBoost manages changing data distributions in fraud detection with a fraud rate of 0.2%. It shows less than 2% degradation under drift. In comparison, XGBoost experiences a 31.8% drop and LightGBM a 42.5% drop

mpsboost

Fast gradient-boosted decision trees for Apple Silicon. A lightweight, sklearn-style Python API powered by MPS and Metal.

lightgbm-no-openmp

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

thundergbm

ThunderGBM: Fast GBDTs and Random Forests on GPUs

autolgbm

LightGBM + Optuna: Auto train LightGBM directly from CSV files, Auto tune them using Optuna, Auto serve best model using FastAPI. Inspired by Abhishek Thakur's AutoXGB.

treegrad

Differentiable Tree Ensembles

catboost-no-sse4

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.

litemort

A memory efficient GBDT on adaptive distributions. Much faster than LightGBM with higher accuracy. Implicit merge operation.

mojotrees

SUPERSEDED by https://github.com/mojolearn/mojolearn (GPU ML in Mojo: GBDT, RF, ExtraTrees, k-means, k-NN, DBSCAN, PCA, OLS). Archived: LightGBM-style GBDT in Mojo.

lightgbm-talaty

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.