Presentation	1998/3/20 An Efficient Way of Using Layered Neural Networks for Multiclass Problems Seiji Ishihara, Takashi Nagano,
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Abstract(in English)	In multiclass problems, the increase of class number causes increase of iteration and decrease of recognition rate when utilizing a feedforward neural network with back-propagation algorithm. Furthermore the total number of parameters in the network increases. Our approach to avoid these troubles is to use a modular network architecture. The modular network consists of small modules. In this paper we present that the total number of parameters in the modular network proposed by us becomes smaller than that in the usual non-modular network as the number of classes increases.
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Keyword(in English)	layered neural network / modular network / multiclass problem
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Conference Information
Committee	NC
Conference Date	1998/3/20(1days)
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Paper Information
Registration To	Neurocomputing (NC)
Language	JPN
Title (in Japanese)	(See Japanese page)
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Title (in English)	An Efficient Way of Using Layered Neural Networks for Multiclass Problems
Sub Title (in English)
Keyword(1)	layered neural network
Keyword(2)	modular network
Keyword(3)	multiclass problem
1st Author's Name	Seiji Ishihara
1st Author's Affiliation	Department of Industrial and System Engineering, College of Engineering, Hosei University()
2nd Author's Name	Takashi Nagano
2nd Author's Affiliation	Department of Industrial and System Engineering, College of Engineering, Hosei University
Date	1998/3/20
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Volume (vol)	vol.97
Number (no)	624
Page	pp.pp.-
#Pages	6
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