吉林大学学报（理学版）2011，Vol.49Issue(3)：498-504,7.
一种改进的Adab00st训练算法
An Improved Adaboost Training Algorithm
摘要
Abstract
In view of the problem of degradation issues as well as the distribution of target class weights adapted to the phenomenon that may arise in the training process of the traditional Adaboost algorithm, the authors introduced a few improved methods to these problems. The article presented a modified Adaboost algorithm based on the adjusted weighted error distribution to limit the expansion weights. In addition, the Adaboost algorithm improved the classifier output forms, i.e. , using output of the probability value instead of the discrete value and increased the detection rate more dramatically. Experiment shows that the test rate of the improved Adaboost algorithm could achieve excellent results in the Inria data set. There are good prospects of application in the field of video security surveillance.关键词
误差分布/Adaboost算法/权重更新/正负误差比/分类器输出Key words
error distribution/ Adaboost algorithm/ weight update/ positive and negative error ratio/ classifier output分类
信息技术与安全科学引用本文复制引用
李文辉,倪洪印..一种改进的Adab00st训练算法[J].吉林大学学报（理学版）,2011,49(3):498-504,7.基金项目
国家自然科学基金(批准号:60873147)、国家高技术研究发展计划863项目基金(批准号:2008AA102224)和吉林省科技发展计划项目(批准号:20060527). （批准号:60873147）
