A rule evaluation support method with learning models based on objective rule evaluation indexes

Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi

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

11 Citations (Scopus)

Abstract

In this paper, we present a novel rule evaluation support method for post-processing of mined results with rule evaluation models based on objective indexes. Post-processing of mined results is one of the key issues to make a data mining process successfully. However, it is difficult for human experts to evaluate many thousands of rules from a large dataset with noises completely. To reduce the costs of rule evaluation procedures, we have developed the rule evaluation support method with rule evaluation models, which are obtained with objective rule evaluation indexes and evaluations of a human expert for each rule. Since the method is needed more accurate rule evaluation models, we have compared learning algorithms to construct rule evaluation models with the actual meningitis data mining result and actual rule sets from UCI datasets. Then we show the availability of our adaptive rule evaluation support method.

Original languageEnglish
Title of host publicationProceedings - Fifth IEEE International Conference on Data Mining, ICDM 2005
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4-7
Number of pages4
ISBN (Print)0769522785, 9780769522784
DOIs
Publication statusPublished - 2005
Event5th IEEE International Conference on Data Mining, ICDM 2005 - Houston, TX, United States
Duration: 2005 Nov 272005 Nov 30

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Other

Other5th IEEE International Conference on Data Mining, ICDM 2005
CountryUnited States
CityHouston, TX
Period05/11/2705/11/30

ASJC Scopus subject areas

  • Engineering(all)

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