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.

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

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.

Behavior-Based Malware Detection using GBDTs

A repository contains more than 12 common statistical machine learning algorithm implementations. 常见机器学习算法原理与实现

🌳 Stacked Gradient Boosting Machines

Collection of ML/DL related papers and notes.

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

ThunderGBM: Fast GBDTs and Random Forests on GPUs

An end-to-end machine learning and data mining framework on Hadoop

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

Classification and Regression problems

A java implementation of LightGBM predicting part

Dataset and experiments from the CIKM 2020 Resource Track

My simplest implementations of common ML algorithms

2020 Spring Fudan University Data Mining Course HW by prof. Zhu Xuening. 复旦大学大数据学院2020年春季课程-数据挖掘（DATA620007）包含数据挖掘算法模型：Linear Regression Model、Logistic Regression Model、Linear Discriminant Analysis、K-Nearest Neighbour、Naive Bayes Classifier、Decision Tree Model、AdaBoost、Gradient Boosting Decision Tree(GBDT)、XGBoost、Random Forest Model、Support Vec…

GBDT (Gradient Boosted Decision Tree: 勾配ブースティング) のpythonによる実装

[ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples

Extreme Gradient Boosting（binary classification)

Ytk-learn is a distributed machine learning library which implements most of popular machine learning algorithms(GBDT, GBRT, Mixture Logistic Regression, Gradient Boosting Soft Tree, Factorization Machines, Field-aware Factorization Machines, Logistic Regression, Softmax).