运筹与管理Issue(1)：67-74,8.
区间型符号数据的特征选择方法
A Feature Selection Method for Symbolic lnterval Data
摘要
Abstract
Feature selection for symbolic interval data can reduce the dimension of data and extract the key fea -tures of data.In order to deal with the feature selection problem , a new method is proposed in this paper .Firstly, Hausdorff distance and Euclidean distance are utilized to measure the similarity between two interval numbers , and an optimization model , which aims to maximize the similarity between each sample and its class center , is established to estimate the feature weights for symbolic interval data .Next, based on the estimated feature selec-tion weights, a classifier is constructed to evaluate the goodness of the weights .Finally, in order to verify the effectiveness of the proposed method , numerical experiments are done in artificially generated data sets and real data sets , respectively . The numerical experiments results show that the proposed algrithm can eliminate irrelevant features and identify features which are relevant to the class labels .关键词
符号数据分析/特征选择/最近邻分类器/区间型数据Key words
symbolic data analysis/feature selection/nearest neighbor classifier/interval data分类
数理科学引用本文复制引用
郭崇慧,刘永超..区间型符号数据的特征选择方法[J].运筹与管理,2015,(1):67-74,8.基金项目
国家自然科学基金资助项目（71171030，71031002）；教育部新世纪优秀人才支持计划 （）
