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.

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.

QAmatch(qa_match)/文本匹配/文本分类/文本embedding/文本聚类/文本检索（bow/ifidf/ngramtf-df/bert/albert/bm25/…/nn/gbdt/xgb/kmeans/dscan/faiss/….）

CTR prediction model based on spark(LR, GBDT, DNN)

python实现GBDT的回归、二分类以及多分类，将算法流程详情进行展示解读并可视化，庖丁解牛地理解GBDT。Gradient Boosting Decision Trees regression, dichotomy and multi-classification are realized based on python, and the details of algorithm flow are displayed, interpreted and visualized to help readers better understand Gradient Boosting Decision Trees

ThunderGBM: Fast GBDTs and Random Forests on GPUs

Perpetual is a high-performance gradient boosting machine. It delivers optimal accuracy in a single run without complex tuning through a simple budget parameter. It features out-of-the-box support for causal ML, continual learning, native calibration, and robust drift monitoring, along with Rust core and zero-copy bindings for Python and R

SIGKDD'2019: DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks

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

Machine Learning Trick : GBDT_Feature Blending Stacking CascadeForest

Gradient boosting decision trees.

A simple GBDT in Python

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).

a python code of applying GBDT+LR for CTR prediction

GNN&GBDT-Guided Fast Optimizing Framework for Large-scale Integer Programming(Ye et al., ICML 2023): https://openreview.net/pdf?id=tX7ajV69wt

A repository contains more than 12 common statistical machine learning algorithm implementations. 常见10余种机器学习算法原理与实现及视频讲解。@月来客栈 出品

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

numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法

《统计学习方法》与常见机器学习模型(GBDT/XGBoost/lightGBM/FM/FFM)的原理讲解与python和类库实现

基于机器学习方法构建多因子选股模型：RandomForest, GBDT, Adaboots, xgboost，MLP, Linear Model, LSTM

MesaTEE GBDT-RS : a fast and secure GBDT library, supporting TEEs such as Intel SGX and ARM TrustZone

Python based GBDT implementation on GPU. Efficient multioutput (multiclass/multilabel/multitask) training

gbdt+lr

Gradient Boosting With Piece-Wise Linear Trees

This project implements random forests and gradient boosted decision trees (GBDT). The latter uses gradient tree boosting. Both use ensemble learning to produce ensembles of decision trees (that is, forests).

This is the official clone for the implementation of the NIPS18 paper Multi-Layered Gradient Boosting Decision Trees (mGBDT) .

One Millisecond Face Alignment with an Ensemble of Regression Trees

该工程是利用python3.6进行“特征提取+分类器”来实现美团评论的文本二分类问题。在特征提取部分提取了6种特征，分类器选择了python里面的包xgboost和lightGBM分别实现提升树和GBDT（梯度提升决策树）。

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