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
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)