boosting

A curated list of gradient boosting research papers with implementations.

pure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks

Combining tree-boosting with Gaussian process and mixed effects models

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

Insanely fast Open Source Computer Vision library for ARM and x86 devices (Up to #50 times faster than OpenCV)

Machine Learning University: Decision Trees and Ensemble Methods

sciblox - Easier Data Science and Machine Learning

Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks [NeurIPS 2019]

Building Decision Trees From Scratch In Python

A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and loss functions.

In depth machine learning resources

An implementation of "Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation" (ASONAM 2019).

Functional gradient boosting based on residual network perception

Analyzing the HR Criteria of a Company and how they promote their Employees and keep Balance between them using Data Analytics, Data Visualizations, and Machine Learning Models for Classification Purposes.

A repository of resources for understanding the concepts of machine learning/deep learning. 

An implementation of the paper "A Short Introduction to Boosting"

We got a stew going!

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"

A face detection program in python using Viola-Jones algorithm.

Rule covering for interpretation and boosting

Python版OpenCVのTracking APIのサンプルです。DaSiamRPNアルゴリズムまで対応しています。

Boosting Functional Regression Models. The current release version can be found on CRAN (http://cran.r-project.org/package=FDboost).

MILBoost and other boosting algorithms, compatible with scikit-learn

My solutions for the USC course CSCI 567: Machine Learning

LogitBoost classification algorithm built on top of scikit-learn

This repository not only contains experience about parameter finetune, but also other in-practice experience such as model ensemble (boosting, bagging and stacking) in Kaggle or other competitions.

Script made to iddle in-game hours on Steam.