电子科技大学学报2012，Vol.41Issue(4)：545-551,7.DOI:10.3969/j.issn.1001-0548.2012.04.013
关于Real AdaBoost算法的分析与改进
Analysis and Improvement on Real AdaBoost Algorithm
摘要
Abstract
The effectiveness, error formula, algorithm flow, and weak classifiers training of Real AdaBoost algorithm are analyzed and proved by a new technique. Real AdaBoost algorithm is improved by weighted combination of weak classifiers and the approximately best combination coefficients are obtained. It is proved that the function of sample weight adjusting method and weak classifiers training method is to guarantee the independence of weak classifiers. Multi-class Real AdaBoost algorithm is proposed based on Bayes statistics deduction. The formula of algorithm and the estimation of classification error are discussed. The training method of weak classifiers is simplified. The estimation of classification error of Gentle AdaBoost is obtained. The effectiveness of the proposed algorithms is verified by the experiment on UCI dataset关键词
分类器组合/集成学习/GentleAda Boost/RealAda BoostKey words
classification combination/ ensemble learning/ Gentle AdaBoost/ Real AdaBoost分类
信息技术与安全科学引用本文复制引用
付忠良..关于Real AdaBoost算法的分析与改进[J].电子科技大学学报,2012,41(4):545-551,7.基金项目
四川省科技支撑计划项目(2008SZ0100,2009SZ0214) （2008SZ0100,2009SZ0214）
