Evaluating learning algorithms composed by a constructive meta-learning scheme for a rule evaluation support method

Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルProceedings - ICDM Workshops 2006 - 6th IEEE International Conference on Data Mining - Workshops
出版社Institute of Electrical and Electronics Engineers Inc.
ページ305-310
ページ数6
ISBN(印刷版)0769527027, 9780769527024
DOI
出版ステータスPublished - 2006

出版物シリーズ

名前Proceedings - IEEE International Conference on Data Mining, ICDM
ISSN(印刷版)1550-4786

ASJC Scopus subject areas

  • Engineering(all)

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