Ordinal Decision Trees

作     者：HU Qinghua CHE Xunjian 

作者机构：School of Energy Science and Engineering Harbin Institute of Technology Harbin Heilongjiang 150001 P. R. China 

出 版 物：《浙江海洋学院学报（自然科学版）》 (Journal of Zhejiang Ocean University(Natural Science Edition))

年 卷 期：2010年第29卷第5期

页      面：450-461页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Natural Science Foundation of China under Grant 60703013 and 10978011 Key Program of National Natural Science Foundation of China under Grant 60932008 National Science Fund for Distinguished Young Scholars under Grant 50925625 China Postdoctoral Science Foundation 

主　　题：ordinal classification rank entropy rank mutual information decision tree 

摘      要：In many decision making tasks,the features and decision are *** ordinal classification learning algorithms have been developed in recent years,it is shown that these algorithms are sensitive to noisy samples and do not work in real-world *** this work,we propose a new measure of feature quality, called rank mutual ***,we design an ordinal decision tree(REOT) construction technique based on rank mutual *** theoretic and experimental analysis shows that the proposed algorithm is effective.