A curated list of gradient boosting research papers with implementations.
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Updated
Mar 16, 2024 - Python
A curated list of gradient boosting research papers with implementations.
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
Python版OpenCVのTracking APIの比較サンプル
A face detection program in python using Viola-Jones algorithm.
A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and loss functions.
An implementation of "Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation" (ASONAM 2019).
MILBoost and other boosting algorithms, compatible with scikit-learn
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks [NeurIPS 2019]
LogitBoost classification algorithm built on top of scikit-learn
Boosting for transfer learning with single / multiple source(s) Regression / Classification
Introduction to tree models with Python
An implementation of the paper "A Short Introduction to Boosting"
Functional gradient boosting based on residual network perception
Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"
We got a stew going!
PKB (Pathway-based Kernel Boosting): use gene expression for classification
Analyzing the binary gender difference in lead roles using statistical machine learning
A simplified implement of Adaptive boosting.
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