Evaluating learning algorithms for a rule evaluation support method

Hidenao Abe, Miho Ohsaki, Shusaku Tsumoto, Takahira Yamaguchi

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

Abstract

In this paper, we present an evaluation of learning algorithms of a novel rule evaluation support method for post-processing of mined results with rule evaluation models based on objective indices. Post-processing of mined results is one of the key processes in a data mining process. However, it is difficult for human experts to completely evaluate several thousands of rules from a large dataset with noises. To reduce the costs in such rule evaluation task, we have developed the rule evaluation support method with rule evaluation models, which learn from objective indices for mined classification rules and evaluations by a human expert for each rule. To enhance adaptability of rule evaluation models, we introduced a constructive meta-learning system to choose proper learning algorithms. Then, we have done the case study on the meningitis data mining as an actual problem.

Original languageEnglish
Title of host publicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Pages3784-3789
Number of pages6
DOIs
Publication statusPublished - 2007
Event2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007 - Montreal, QC, Canada
Duration: 2007 Oct 72007 Oct 10

Other

Other2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
CountryCanada
CityMontreal, QC
Period07/10/707/10/10

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Abe, H., Ohsaki, M., Tsumoto, S., & Yamaguchi, T. (2007). Evaluating learning algorithms for a rule evaluation support method. In Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics (pp. 3784-3789). [4413881] https://doi.org/10.1109/ICSMC.2007.4413881