Mapping of nearest neighbor for classification

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. B...

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Bibliographic Details
Main Authors: Ishii, Naohiro, Torii, Ippei, Yongguang Bao, Tanaka, Hidekazu
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
classification
Data analysis
dimension reduction
Equations
Euclidean distance
nearest neighbor
reduct
Training
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Summary: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.
DOI:10.1109/ICIS.2013.6607819