期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2016
卷号：7
期号：3
页码：1111-1115
出版社：TechScience Publications
摘要：Feature selection has become an interestingresearch topic in recent years. It is an effective method totackle the data with high dimension. The underlying structurehas been ignored by the previous feature selection method andit determines the feature individually. Considering this fact wefocus on the problem where feature possess some groupstructure. To solve this problem we present group featureselection method at group level to execute feature selection. Itsobjective is to execute the feature selection in within the groupand between the group of features that select discriminativefeatures and remove redundant features to obtain optimalsubset. We demonstrate our method on benchmark data setsand perform the task to achieve classification accuracy.
关键词：feature selection; group structure; redundant;classification.
