A logical approach to fuzzy data analysis

Churn Jung Liau, Duen-Ren Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

In this paper, we investigate the extraction of fuzzy rules from data tables based on possibility theory. A possibilistic decision language is used to represent the extracted fuzzy rules. The algorithm for rule extraction is presented and the complexity analysis is carried out. Since the results of the rule induction process strongly depend on the representation language, we also discuss some approach for dynamic adjustment of the language based on the data.

Original languageEnglish
Title of host publicationPrinciples of Data Mining and Knowledge Discovery - 3d European Conference, PKDD 1999, Proceedings
EditorsJan Rauch, Jan M. Żytkow
PublisherSpringer Verlag
Pages412-417
Number of pages6
ISBN (Print)3540664904, 9783540664901
DOIs
StatePublished - 1 Jan 1999
Event3rd European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 1999 - Prague, Czech Republic
Duration: 15 Sep 199918 Sep 1999

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1704
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 1999
CountryCzech Republic
CityPrague
Period15/09/9918/09/99

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