Presentation 2004/2/13
Pattern Recognition Using Average Patterns of Categorical K-Nearest Neighbors
Seiji HOTTA, Senya KIYASU, Sueharu MIYAHARA,
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Abstract(in English) The typical non-parametric method of pattern recognition "κ-nearest neighbor rule (κNN)" is carried out by counting the labels of the κ-nearest training samples to a test sample. This method collects the κ-nearest neighbors without taking into account a category and outputs the category of the test sample by using only the labels of training sets. This paper presents a classifier that outputs the category of a test sample based on the distance between the test sample and the average patterns, which are calculated using the κ-nearest neighbors belonging to individual categories. A kernel method can be applied to this classifier for improving recognition rates. Performance of the proposed method is examined using handwritten digit patterns and artificial sets of patterns.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) κ-nearest neighbor / average pattern / kernel method / handwritten digit recognition
Paper # TL2003-69,PRMU2003-255
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Committee TL
Conference Date 2004/2/13(1days)
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Registration To Thought and Language (TL)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Pattern Recognition Using Average Patterns of Categorical K-Nearest Neighbors
Sub Title (in English)
Keyword(1) κ-nearest neighbor
Keyword(2) average pattern
Keyword(3) kernel method
Keyword(4) handwritten digit recognition
1st Author's Name Seiji HOTTA
1st Author's Affiliation Department of Computer and Information Sciences, Nagasaki University()
2nd Author's Name Senya KIYASU
2nd Author's Affiliation Department of Computer and Information Sciences, Nagasaki University
3rd Author's Name Sueharu MIYAHARA
3rd Author's Affiliation Department of Computer and Information Sciences, Nagasaki University
Date 2004/2/13
Paper # TL2003-69,PRMU2003-255
Volume (vol) vol.103
Number (no) 657
Page pp.pp.-
#Pages 6
Date of Issue