論文

査読有り
2015年

Classification on Nonlinear Mapping of Reducts Based on Nearest Neighbor Relation

2015 IEEE/ACIS 14TH INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCE (ICIS)
  • Naohiro Ishii
  • ,
  • Ippei Torii
  • ,
  • Naoto Mukai
  • ,
  • KazunoriIwata
  • ,
  • Toyoshiro Nakashima

開始ページ
491
終了ページ
496
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
出版者・発行元
IEEE

Dimension reduction of data is an important theme in the data processing and on the web to represent and manipulate higher dimensional data. Rough set is fundamental and useful to process higher dimensional data. Reduct in the rough set is a minimal subset of features, which has the same discernible power as the entire features in the higher dimensional scheme. It is shown that nearest neighbor relation with minimal distance introduced here has a basic information for classification. In this paper, a new reduct generation method based on the nearest neighbor relation with minimal distance is proposed. To improve the classification accuracy of reducts, we develop a nonlinear mapping method on the nearest neighbor relation, which makes vector data relation among neighbor data and preserves data ordering

リンク情報
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000380504300082&DestApp=WOS_CPL
ID情報
  • Web of Science ID : WOS:000380504300082

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