【推荐】Kaggle大牛讲解Gradient Boosting基础

If linear regression was a Toyota Camry, then gradient boosting would be a UH-60 Blackhawk Helicopter.  A particular implementation of gradient boosting, XGBoost, is consistently used to win machine learning competitions on Kaggle. Unfortunately many practitioners (including my former self) use it as a black box.  It’s also been butchered to death by a host of drive-by data scientists’ blogs.  As such, the purpose of this article is to lay the groundwork for classical gradient boosting, intuitively and comprehensively.

Motivation

We’ll start with a simple example.  We want to predict a person’s age based on whether they play video games, enjoy gardening, and their preference on wearing hats.  Our objective is to minimize squared error.  We have these nine training samples to build our model.

链接：

http://blog.kaggle.com/2017/01/23/a-kaggle-master-explains-gradient-boosting/

原文链接：

http://weibo.com/1402400261/EsfeHFE5r?from=page_1005051402400261_profile&wvr=6&mod=weibotime&type=comment#_rnd1485255724349