DocumentCode :
1796492
Title :
Generation of reducts based on nearest neighbor relation
Author :
Ishii, Naohiro ; Torii, Ippei ; Nakashima, Takayoshi ; Iwata, Keiji
Author_Institution :
Dept. of Inf. Sci., Aichi Inst. of Technol., Toyota, Japan
fYear :
2014
fDate :
June 30 2014-July 2 2014
Firstpage :
1
Lastpage :
6
Abstract :
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. Nearest neighbor relation between different classes has a basic information for classification. We propose here a reduct generation method based on the nearest neighbor relation. To characterize 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.
Keywords :
graph theory; pattern classification; rough set theory; data processing; dimension reduction; graph mapping method; higher dimensional data; nearest neighbor relation; reduct generation method; rough set theory; Absorption; Accuracy; Data analysis; Educational institutions; Equations; Sufficient conditions; classification; mapping ofreducts; nearest neighbor relation; reduct; reduct eneration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2014 15th IEEE/ACIS International Conference on
Conference_Location :
Las Vegas, NV
Type :
conf
DOI :
10.1109/SNPD.2014.6888692
Filename :
6888692
Link To Document :
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