Computer Science ›› 2018, Vol. 45 ›› Issue (10): 43-46.doi: 10.11896/j.issn.1002-137X.2018.10.008

• CGCKD 2018 • Previous Articles     Next Articles

Feature Selection Algorithm Based on Segmentation Strategy

JIAO Na   

  1. Department of Information Science and Technology,East China University of Political Science and Law,Shanghai 201620,China
  • Received:2018-04-17 Online:2018-11-05 Published:2018-11-05

Abstract: Feature selection is a key issue in rough sets.The theory of rough sets is an efficient tool for reducing redundancy.At pre-sent,there are many items and features in a large table,but few methods can gain better performance for big data table.The idea of segmentation was introduced in this paper.A big data table is divided into several small tables,and selection results are joined together to solve feature selection problem of the original table.To evaluate the performance of the proposed method,this paper applied it to the benchmark data sets.Experimental results illustrate that the proposed method is effective.

Key words: Core-table, Feature selection, Redundant-table, Rough set theory, Segmentation

CLC Number: 

  • TP181
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