#Awesome XGBoost
Welcome to the wonderland of XGBoost. This page contains a curated list of awesome XGBoost examples, tutorials and blogs. It is inspired by awesom-MXnet, awesome-php and awesome-machine-learning.
- Contribution of examples, benchmarks is more than welcome!
- If you like to share how you use xgboost to solve your problem, send a pull request:)
- If you want to contribute to this list and the examples, please open a new pull request.
##List of examples
This is a list of short codes introducing different functionalities of xgboost packages.
- Basic walkthrough of packages python R Julia
- Customize loss function, and evaluation metric python R Julia
- Boosting from existing prediction python R Julia
- Predicting using first n trees python R Julia
- Generalized Linear Model python R Julia
- Cross validation python R Julia
- Predicting leaf indices python R
Most of examples in this section are based on CLI or python version. However, the parameter settings can be applied to all versions
"Over the last six months, a new algorithm has come up on Kaggle winning every single competition in this category, it is an algorithm called XGBoost." -- Anthony Goldbloom, Founder & CEO of Kaggle (from his presentation "What Is Winning on Kaggle?" youtube link)
- XGBoost helps Marios Michailidis, Mathias Müller and HJ van Veen to win (1st place) the Dato Truely Native? competition. Check out the interview from Kaggle.
- XGBoost helps Vlad Mironov, Alexander Guschin to win (1st place) the CERN LHCb experiment Flavour of Physics competition. Check out the interview from Kaggle.
- XGBoost helps Josef Slavicek to win (3rd place) the CERN LHCb experiment Flavour of Physics competition. Check out the interview from Kaggle.
- XGBoost helps Mario Filho, Josef Feigl, Lucas, Gilberto to win (1st place) the Caterpillar Tube Pricing competition. Check out the interview from Kaggle.
- XGBoost helps Qingchen Wang to win (1st place) the Liberty Mutual Property Inspection. Check out the interview from Kaggle.
- XGBoost helps Chenglong Chen to win (1st place) the Crowdflower Search Results Relevance. Check out the Winning solution.
- XGBoost helps Alexandre Barachant (“Cat”) and Rafał Cycoń (“Dog”) to win (1st place) the Grasp-and-Lift EEG Detection. Check out the interview from Kaggle.
- XGBoost helps Halla Yang to win (2nd place) the Recruit Coupon Purchase Prediction Challenge. Check out the interview from Kaggle.
- XGBoost helps Owen Zhang to win (1st place) the Avito Context Ad Clicks competition. Check out the interview from Kaggle.
- There are many other great winning solutions and interviews, but this list is too small to put all of them here. Please send pull requests if important ones appear.
- "Open Source Tools & Data Science Competitions" by Owen Zhang - XGBoost parameter tuning tips
- "Tips for data science competitions" by Owen Zhang - Page 14
- "XGBoost - eXtreme Gradient Boosting" by Tong He
- "How to use XGBoost algorithm in R in easy steps" by TAVISH SRIVASTAVA (Chinese Translation 中文翻译 by HarryZhu)
- "Kaggle Solution: What’s Cooking ? (Text Mining Competition)" by MANISH SARASWAT
- "Better Optimization with Repeated Cross Validation and the XGBoost model - Machine Learning with R)" by Manuel Amunategui (Youtube Link) (Github Link)
- "XGBoost Rossman Parameter Tuning" by Norbert Kozlowski
- "Featurizing log data before XGBoost" by Xavier Conort, Owen Zhang etc
- "West Nile Virus Competition Benchmarks & Tutorials" by Anna Montoya
- "Ensemble Decision Tree with XGBoost" by Bing Xu
- "Notes on eXtreme Gradient Boosting" by ARSHAK NAVRUZYAN (iPython Notebook)
- BayesBoost - Bayesian Optimization using xgboost and sklearn API
- John Chambers Award - 2016 Winner: XGBoost, by Tong He (Simon Fraser University) and Tianqi Chen (University of Washington)