A curated list of gradient boosting research papers with implementations.

Represent trained machine learning models as Pyomo optimization formulations

Hybrid model of Gradient Boosting Trees and Logistic Regression (GBDT+LR) on Spark

An example project that predicts house prices for a Kaggle competition using a Gradient Boosted Machine.

Library for Multi-objective optimization in Gradient Boosted Trees

Multiobjective black-box optimization using gradient-boosted trees

A "build to learn" Alpha Zero implementation using Gradient Boosted Decision Trees (LightGBM)

Machine Learning Tool Box

Influence Estimation for Gradient-Boosted Decision Trees

Machine learning multiclassification task in particle physics experiment (Belle II) with deep neural networks (DNN) and gradient boosted decision trees (XGBoost).

OncoNetExplainer: Explainable Prediction of Cancer Types Based on Gene Expression Data

ML models trained on the SARCOS dataset

Sequential skip prediction using deep learning and ensembles

PhishyAI trains ML models for Phishy, a Gmail extension which leverages ML to detect phishing attempts in all incoming emails

An implementation of the algorithms from the camera-ready version of the paper "Coresets for Decision Trees of Signals" (NeurIPS'2021) by Ibrahim Jubran, Ernesto Evgeniy Sanches Shayda, Ilan Newman, and Dan Feldman.

Projects for ECE 475 - Freq. Machine Learning

Simple Implementation of Gradient Boosted Trees

sentiment analysis using the movie reviews from the imdb database

In this project I wanted to predict attrition based on employee data. The data is an artificial dataset from IBM data scientists. It contains data for 1470 employees. Te dataset contains the following information per employee:

Different feature selection methods like SVD, SelectKBest, RFE are used to choose best features, then different machine learning algorithms like Random Forest, Gradient Boosting Tree, XGBoost together with GridsearchCV etc are applied and compared to choose the good model which is the best fit for the dataset.