会议专题

Improve the Performance of Random Forests by Introducing Weight Update Technique

We investigate approaches to improve the performance of random forests by introducing weight update and bootstrap techniques and propose a new algorithm that combine these techniques smoothly. Experiments show that the proposed approach performs better than the original RF and works well with different weight update techniques used by three most popular version of AdaBoost. At the same time there is no more parameters to adjust compared with RF.

AdaBoost random forests bagging bootstrap CART

Binxuan Sun Jiarong Luo Shuangbao Shu Erbing Xue

College of Science,Donghua University Shanghai,China

国际会议

2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics(第二届智能人机系统与控制论国际学术会议 IHMSC 2010)

南京

英文

34-37

2010-08-26(万方平台首次上网日期,不代表论文的发表时间)