基于Double-Bagging决策树的基因微阵列数据研究  

Study on Gene Micro-array Data Based on Double-Bagging Decision-making Tree

作　　者：袁科[1] 

机构地区：[1]湖北汽车工业学院电气与信息工程学院,湖北十堰442002

出　　处：《湖北汽车工业学院学报》2009年第2期40-43,共4页Journal of Hubei University Of Automotive Technology

摘　　要：Bagging通过组合不稳定的分类器在很大程度上降低了"弱"学习算法的分类误差。基于Torsten等人提出的Double-Bagging算法,本文对其加以修改并应用于基因微阵列数据的处理。在给定的训练数据集和测试集上试验并比较了多种分类器,结果表明Double-Bagging决策树分类精确度优于Bagging决策树和C4.5算法。The three algorithms： Bagging, Double-Bagging and C4.5 were introduced, of which Dou ble-Bagging algorithm was modified and the modified algorithm was applied to gene micro-array data processing. The experiment was done on the specific training data set and the test collection, and many kinds of sorters were compared. The results show that the classification precision of the Dou ble-Bagging decision-making tree is superior to the Bagging decision-making tree and C4.5.

关 键 词：Double—Bagging算法 Double-Bagging决策树 基因微阵列数据 分类器 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]