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#

gbrt

Here are 11 public repositories matching this topic...

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

  • UpdatedFeb 20, 2026
  • C++
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.

  • UpdatedFeb 19, 2026
  • C++

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

  • UpdatedJul 9, 2025
  • Python

A 100%-Julia implementation of Gradient-Boosting Regression Tree algorithms

  • UpdatedNov 28, 2024
  • Julia

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

  • UpdatedJul 12, 2025
  • C++

Show how to perform fast retraining with LightGBM in different business cases

  • UpdatedJul 18, 2019
  • Jupyter Notebook

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.

  • UpdatedFeb 13, 2022
  • Python

This repository provides an example of dataset preprocessing, GBRT (Gradient Boosted Regression Tree) model training and evaluation, model tuning and finally model serving (REST API) in a containerized environment using MLflow tracking, projects and models modules.

  • UpdatedAug 7, 2022
  • Jupyter Notebook

This Repo is a Job for building a Regression Model and Deploy the Model using Flask and host at heroku

  • UpdatedJul 29, 2022
  • Jupyter Notebook

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