A Study on Quantitative Association Rules Mining Algorithm Based on Clustering Algorithm(<Special Issue>COMPUTATIONAL INTELLIGENCE)

スポンサーリンク

概要

• 論文の詳細を見る

• In order to develop a data mining system for huge database mainly composed of numerical attributes, there exists necessary process to decide valid quantization of the numerical attributes. Though the clustering algorithm can provide useful information for the quantization problem, it is difficult to formulate appropriate clusters for rule extraction in terms of appropriate dimension, cluster size, and shape. In this paper, we propose a new method of quantitative association rules extraction that can quantize the attribute by applying clustering algorithm and extract rules simultaneously. From the results of numerical experiments using benchmark data, the method is found to be effective for actual applications.

• バイオメディカル・ファジィ・システム学会の論文

著者

• WATANABE Toshihiko

  Faculty of Engineering, Osaka Electo-Communication University

• TAKAHASHI Hirokazu

  NEC Soft Corporation

関連論文

• A Study on Quantitative Association Rules Mining Algorithm Based on Clustering Algorithm(COMPUTATIONAL INTELLIGENCE)

スポンサーリンク