Presentation 1997/11/13
Generation of Default Rules Based on AIC
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Abstract(in English) The method to generate default rules of causal relation is discribed. We extend the definition of association rules in order to deal with uncertain attribute values. New methods to filter out irrelevant rules based on AIC and how to construct Bayesian networks are proposed. Finally, a scheme of Causal Law Mining is proposed as an integration of techniques describe in the paper.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Default Logic / Causal Law / Data Mining / Akaike Information Criteria / Bayesian Networks
Paper # AI97-27
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Conference Information
Committee AI
Conference Date 1997/11/13(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) Generation of Default Rules Based on AIC
Sub Title (in English)
Keyword(1) Default Logic
Keyword(2) Causal Law
Keyword(3) Data Mining
Keyword(4) Akaike Information Criteria
Keyword(5) Bayesian Networks
1st Author's Name Kazunori MATSUMOTO
1st Author's Affiliation KDD Research and Development Laboratories()
2nd Author's Name Kazuo HASHIMOTO
2nd Author's Affiliation KDD Research and Development Laboratories
Date 1997/11/13
Paper # AI97-27
Volume (vol) vol.97
Number (no) 373
Page pp.pp.-
#Pages 6
Date of Issue