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Paper Abstract and Keywords
Presentation 2007-01-17 11:20
Midpoint Validation Method of Neural Networks for Pattern Classification Problems
Yasunori Sakamoto (Toyama Univ.), Hiroki Tamura, Koichi Tanno (Miyazaki Univ.), Kazuya Yamashita, Masahiro Ishii, Masaaki Toudou (Toyama Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose a midpoint validation method which improves the generalization of neural networks. The problem associated with the former cross-validation method is that efficiency is infected due to the separation of training data into two or N set. As for the proposed method, it creates new data from the known training data and computes a set of criteria using the newly created data and the previous training data. The implementation is easy since there is no unnecessary processing involved in separating the data into two or N sets. The advantage of the proposed method is that the method becomes much more efficient compared to the former method due to the numerical simulation used.
We compare its performance with those of the Support Vector Machine (abbr. SVM), Multilayer Perceptron (abbr. MLP), Radial Basis Function (abbr. RBF) and proposed method on several benchmark problems. The results obtained from the simulation carried out shows the effectiveness of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) Neural Network / Cross-Validation / Ionosphere data / Pima-indians-diabetes data / Wisconsin breast cancer data / / /  
Reference Info. IEICE Tech. Rep., vol. 106, no. 451, NLP2006-114, pp. 19-24, Jan. 2007.
Paper # NLP2006-114 
Date of Issue 2007-01-10 (NLP) 
ISSN Print edition: ISSN 0913-5685
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Conference Information
Committee NLP  
Conference Date 2007-01-17 - 2007-01-18 
Place (in Japanese) (See Japanese page) 
Place (in English)  
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Paper Information
Registration To NLP 
Conference Code 2007-01-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Midpoint Validation Method of Neural Networks for Pattern Classification Problems 
Sub Title (in English)  
Keyword(1) Neural Network  
Keyword(2) Cross-Validation  
Keyword(3) Ionosphere data  
Keyword(4) Pima-indians-diabetes data  
Keyword(5) Wisconsin breast cancer data  
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1st Author's Name Yasunori Sakamoto  
1st Author's Affiliation University of TOYAMA (Toyama Univ.)
2nd Author's Name Hiroki Tamura  
2nd Author's Affiliation University of MIYAZAKI (Miyazaki Univ.)
3rd Author's Name Koichi Tanno  
3rd Author's Affiliation University of MIYAZAKI (Miyazaki Univ.)
4th Author's Name Kazuya Yamashita  
4th Author's Affiliation University of TOYAMA (Toyama Univ.)
5th Author's Name Masahiro Ishii  
5th Author's Affiliation University of TOYAMA (Toyama Univ.)
6th Author's Name Masaaki Toudou  
6th Author's Affiliation University of TOYAMA (Toyama Univ.)
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Speaker Author-1 
Date Time 2007-01-17 11:20:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # NLP2006-114 
Volume (vol) vol.106 
Number (no) no.451 
Page pp.19-24 
#Pages
Date of Issue 2007-01-10 (NLP) 


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