Discovery of surprising exception rules based on intensity of implication

Einoshin Suzuki, Yves Kodratoff

Research output: Chapter in Book/Report/Conference proceedingConference contribution

39 Citations (Scopus)

Abstract

This paper presents an algorithm for discovering surprising exception rules from data sets. An exception rule, which is defined as a deviational pattern to a common sense, exhibits unexpectedness and is sometimes extremely useful. A domain-independent approach, PEDRE, exists for the simultaneous discovery of exception rules and their common sense rules. However, PEDRE, being too conservative, have difficulty in discovering surprising rules. Historic exception discoveries show that surprise is often linked with interestingness. In order to formalize this notion we propose a novel approach by improving PEDRE. First, we reformalize the problem and settle a looser constraints on the reliability of an exception rule. Then, in order to screen out uninteresting rules, we introduce, for an exception rule, an evaluation criterion of surprise by modifying intensity of implication, which is based on significance. Our approach has been validated using data sets from the UCI repository.

Original languageEnglish
Title of host publicationPrinciples of Data Mining and Knowledge Discovery - 2nd European Symposium, PKDD 1998, Proceedings
EditorsJan M. Zytkow, Mohamed Quafafou
PublisherSpringer Verlag
Pages10-18
Number of pages9
ISBN (Print)3540650687, 9783540650683
Publication statusPublished - Jan 1 1998
Event2nd European Symposium on Principles of Data Mining and Knowledge Discovery in Databases, PKDD 1998 - Nantes, France
Duration: Sep 23 1998Sep 26 1998

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1510
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd European Symposium on Principles of Data Mining and Knowledge Discovery in Databases, PKDD 1998
CountryFrance
CityNantes
Period9/23/989/26/98

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Suzuki, E., & Kodratoff, Y. (1998). Discovery of surprising exception rules based on intensity of implication. In J. M. Zytkow, & M. Quafafou (Eds.), Principles of Data Mining and Knowledge Discovery - 2nd European Symposium, PKDD 1998, Proceedings (pp. 10-18). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1510). Springer Verlag.