1.txt

来自「This complete matlab for neural network」· 文本 代码 · 共 38 行

发信人: GzLi (笑梨), 信区: DataMining
标  题:  Machine Learning 47(2/3) <1>
发信站: 南京大学小百合站 (Thu Jul 18 00:44:54 2002), 站内信件

篇名： Boosting Methods for Regression 
刊名： Machine Learning 
ISSN： 0885-6125 
卷期： 47 卷 2/3 期 出版日期： 200205/06  
页码： 从 153 页到 200 页共 48 页 
作者： Duffy Nigel   Computer Science Department, University of California
, Santa Cruz, Santa Cruz, CA 95064, USA. [e-mail]
 
Helmbold David   Computer Science Department, University of California, Santa
 Cruz, Santa Cruz, CA 95064, USA. [e-mail]
 
 
文摘： 
In this paper we examine ensemble methods for regression that leverage or
 “boost” base regressors by iteratively calling them on modified samples
. The most successful leveraging algorithm for classification is AdaBoost
, an algorithm that requires only modest assumptions on the base learning
 method for its strong theoretical guarantees. We present several gradient
 descent leveraging algorithms for regression and prove AdaBoost-style bounds
 on their sample errors using intuitive assumptions on the base learners.
 We bound the complexity of the regression functions produced in order to
 derive PAC-style bounds on their generalization errors. Experiments validate
 our theoretical results.
 


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※ 修改:．GzLi 于 Jul 18 00:46:31 修改本文．[FROM: 211.80.38.29]
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