XGBoost Reference

XGBoost를 공부하기 위하여 여러 참고자료를 정리해보았습니다.

• Demystifying Maths of Gradient Boosting

https://towardsdatascience.com/demystifying-maths-of-gradient-boosting-bd5715e82b7c

수리적으로 하나씩 설명하는 모습이 제가 지향하는 블로그 포스팅이었습니다.

• The Gradient Boosters III: XGBoost

https://deep-and-shallow.com/2020/02/12/the-gradient-boosters-iii-xgboost/

• Block-distributed Gradient Boosted Trees

http://tvas.me/articles/2019/08/26/Block-Distributed-Gradient-Boosted-Trees.html

• Comparing Decision Tree Algorithms: Random Forest Vs. XGBoost

https://www.activestate.com/blog/comparing-decision-tree-algorithms-random-forest-vs-xgboost/

• Xgboost: machine learning algorithm you can’t know

https://developpaper.com/xgboost-machine-learning-algorithm-you-cant-know/

• Beginners Tutorial on XGBoost and Parameter Tuning in R

https://www.hackerearth.com/practice/machine-learning/machine-learning-algorithms/beginners-tutorial-on-xgboost-parameter-tuning-r/tutorial/

간단한 설명 이후, R 구현을 진행. 파라미터에 대한 이해를 돕습니다.

• XGBoost: A Concise Technical Overview

https://www.kdnuggets.com/2017/10/xgboost-concise-technical-overview.html

• XGboost 논문 따라가기

http://machinelearningkorea.com/2019/09/28/xgboost-%EB%85%BC%EB%AC%B8%EB%94%B0%EB%9D%BC%EA%B0%80%EA%B8%B0/

• Why XGBoost Is So Effective?

https://towardsdatascience.com/why-xgboost-is-so-effective-3a193951e289

Gradient Boosting

• Gradient Boosting Algorithm의 직관적인 이해

https://3months.tistory.com/368

Related Math

Closed Form

http://wanochoi.com/?p=5061

Taylor Expansion / Series

• Introduction to Taylor’s theorem for multivariable functions

https://darkpgmr.tistory.com/59