DocumentCode :
635499
Title :
Mapping of nearest neighbor for classification
Author :
Ishii, Naohiro ; Torii, Ippei ; Yongguang Bao ; Tanaka, Hiroya
Author_Institution :
Dept. of Inf. Sci., Aichi Inst. of Technol., Toyota, Japan
fYear :
2013
fDate :
16-20 June 2013
Firstpage :
121
Lastpage :
126
Abstract :
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.
Keywords :
graph theory; pattern classification; classification accuracy; data classification; data dimension reduction; data processing; data reducts application; graph mapping method; nearest neighbor mapping; Accuracy; Data analysis; Equations; Euclidean distance; Training; classification; dimension reduction; nearest neighbor; reduct;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Information Science (ICIS), 2013 IEEE/ACIS 12th International Conference on
Conference_Location :
Niigata
Type :
conf
DOI :
10.1109/ICIS.2013.6607819
Filename :
6607819
Link To Document :
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