Mapping of Nearest Neighbor for Classification

被引:0
作者
Ishii, Naohiro [1 ]
Torii, Ippei [1 ]
Bao, Yongguang [2 ]
Tanaka, Hidekazu [3 ]
机构
[1] Aichi Inst Technol, Dept Informat Sci, Toyota 47003, Japan
[2] Aichi Informat Syst, Kariya, Aichi, Japan
[3] Daido Univ, Nagoya, Aichi, Japan
来源
2013 IEEE/ACIS 12TH INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCE (ICIS) | 2013年
关键词
classification; reduct; nearest neighbor; dimension reduction;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Dimension reduction of data is an important theme in the data processing and on the web to represent and manipulate higher dimensional data. Reduct in the rough set is a minimal subset of features, which has almost the same discernible power as the entire features in the higher dimensional scheme. But, there are problems in the application of reducts for classification. Here, we develop a method which connects reducts and the nearest neighbor method to classify data with higher classification accuracy. To improve the classification ability of reducts, we develop a new graph mapping method of the nearest neighbor based on reducts and weighted modified reducts for the classification with higher accuracy. Then, the mapping method is useful and the weighted modified reduct classifies with higher accuracy.
引用
收藏
页码:121 / +
页数:6
相关论文
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