Evaluating hypothesis-driven exception-rule discovery with medical data sets

Einoshin Suzuki, Shusaku Tsumoto

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

15 Citations (Scopus)

Abstract

This paper presents a validation, with two common medical data sets, of exception-rule discovery based on a hypothesis-driven approach. The analysis confirmed the effectiveness of the approach in discovering valid, novel and surprising knowledge.

Original languageEnglish
Title of host publicationKnowledge Discovery and Data Mining
Subtitle of host publicationCurrent Issues and New Applications - 4th Pacific-Asia Conference, PAKDD 2000, Proceedings
EditorsArbee L.P. Chen, Takao Terano, Huan Liu
PublisherSpringer Verlag
Pages208-211
Number of pages4
ISBN (Print)3540673822, 9783540673828
Publication statusPublished - Jan 1 2000
Externally publishedYes
Event4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2000 - Kyoto, Japan
Duration: Apr 18 2000Apr 20 2000

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1805
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2000
CountryJapan
CityKyoto
Period4/18/004/20/00

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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