TWO STAGES BASED ADAPTIVE SAMPLING BOOSTING METHOD

摘要：

To improve learning performance of Boosting method, Boosting learning procedure is divided into two sequential stages which are named reducing fitting error stage and reducing variance stage according to the idea of generalization error of Boosting method composed of bias and variance which was originally proposed by Breiman. Traditional sampling methods such as roulette wheel selection is suitable for the learning procedure of reducing fitting error stage, and based on the characteristics of reducing variance stage, a new sampling method is proposed named SS method. Based on CSP and SS sampling methods, a new two stages based adaptive sampling Boosting method named ASSBoosting is proposed, which according to the different characteristics of the two learning stages adaptively adopts sampling methods by the comparison of the prediction error caused by the two methods. The results of simulation confirm these findings.

关键词： Two stages CEBoosting method reducing fitting error stage reducing bias stage adaptive sampling strategy

作者: CONG-MAN WANG HUI-ZHI YANG FA-CHAO LI RUI-XUE FU

作者单位: College of Economics & Management, Hebei University of Science and Technology, Shijiazhuang 050018, Shijiazhuang University of Economics, Shijiazhuang 050031, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 2925-2927

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）