forust
Gradient booster
A package implementing a lightweight gradient boosted decision tree algorithm
A lightweight gradient boosted decision tree package.
67 stars
6 watching
6 forks
Language: Rust
last commit: 6 months ago aimachine-learningpyo3pythonrustxgboostxgboost-algorithm
Related projects:
| Repository | Description | Stars |
|---|---|---|
 springdaisy/gbdt | An implementation of Gradient Boosted Decision Trees with sparse output for high-dimensional data | 0 |
 dmlc/xgboost.jl | A Julia package implementing a distributed gradient boosting framework with efficient linear model solver and tree learning algorithms. | 289 |
 tqchen/xgboost | An optimized distributed gradient boosting library for machine learning | 571 |
 ys-l/pgbm | An implementation of a parallelized gradient boosting algorithm for regression tasks | 2 |
 arogozhnikov/infiniteboost | A software package implementing an ensemble boosting method with gradient descent | 184 |
 stanfordmlgroup/ngboost | A Python library implementing a machine learning boosting framework with probabilistic prediction capabilities | 1,654 |
 chasedehan/boostaroota | An algorithm for fast feature selection using XGBoost and other tree-based classifiers | 219 |
 kingfengji/mgbdt | An implementation of a gradient boosting decision tree algorithm with target propagation capabilities | 102 |
 gbdt-pl/gbdt-pl | An implementation of a gradient boosting algorithm with piece-wise linear regression trees for efficient machine learning model training | 149 |
 ankane/xgboost-ruby | High-performance machine learning library with a Ruby interface to XGBoost gradient boosting algorithm | 105 |
 bsharchilev/influence_boosting | This repository implements methods to find influential training samples in Gradient Boosted Decision Trees ensembles | 67 |
 gbm-developers/gbm | An R package providing extensions to AdaBoost and gradient boosting machine algorithms for regression and other tasks. | 51 |
 harshakokel/kigb | An open-source software framework that integrates human advice into gradient boosting decision trees for improved performance in machine learning tasks. | 8 |
 serengil/chefboost | A Python library providing a lightweight framework for building decision trees with categorical feature support | 460 |
 nnikolaou/cost-sensitive-boosting-tutorial | Provides tools and methods for handling asymmetric classification problems in machine learning | 26 |