Greedy Function Approximation:A Gradient Boosting Machine

 

https://statweb.stanford.edu/~jhf/ftp/trebst.pdf

 

 

page10


90% to 95% of the observations were often deleted without sacrificing accuracy of the
estimates,using either influence measure.

 

 

 

 

 

 

【解释regularization】

page12
5 Regularization
In prediction problems,fitting the training data too closely can be counterproductive.

 

posted @ 2017-09-29 20:03  papering  阅读(428)  评论(0)  编辑  收藏  举报