Presentation	2007-03-28 Acquiring Classification Rules by using Adaptive Resonance Theory You Nasu, Takeshi Yamada, Hiroaki Ueda, Kenichi Takahashi, Tetsuhiro Miyahara,
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Abstract(in English)	We propose two on-line classification methods, ARTMAP_ and ARTMAP_, which are based on adaptive resonance theory. ARTMAP_ classifies cases on the basis of Euclidean distance and it incorporates category merging as a generalization technique. ARTMAP_ is the modification of ARTMAP_ to consider the importance of each attribute. The importance of attributes is updated through generalizing and specializing classification rules. Experimental results show that ARTMAP_ acquires better classification rules with fewer categories than ARTMAP_, fuzzy ARTMAP and C4.5.
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Keyword(in English)	classification / adaptive resonance theory / match tracking / category merging
Paper #	AI2006-70,KBSE2006-78
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Committee	AI
Conference Date	2007/3/21(1days)
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Paper Information
Registration To	Artificial Intelligence and Knowledge-Based Processing (AI)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Acquiring Classification Rules by using Adaptive Resonance Theory
Sub Title (in English)
Keyword(1)	classification
Keyword(2)	adaptive resonance theory
Keyword(3)	match tracking
Keyword(4)	category merging
1st Author's Name	You Nasu
1st Author's Affiliation	Hiroshima City University()
2nd Author's Name	Takeshi Yamada
2nd Author's Affiliation	Hiroshima City University
3rd Author's Name	Hiroaki Ueda
3rd Author's Affiliation	Hiroshima City University
4th Author's Name	Kenichi Takahashi
4th Author's Affiliation	Hiroshima City University
5th Author's Name	Tetsuhiro Miyahara
5th Author's Affiliation	Hiroshima City University
Date	2007-03-28
Paper #	AI2006-70,KBSE2006-78
Volume (vol)	vol.106
Number (no)	617
Page	pp.pp.-
#Pages	4
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