Authors: Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
Addresses: Department of Medical Informatics, Shimane University, School of Medicine, 89-1 Enya-cho, Izumo, Shimane 693-8501, Japan. ' Department of Medical Informatics, Shimane University, School of Medicine, 89-1 Enya-cho, Izumo, Shimane 693-8501, Japan. ' Faculty of Science and Engineering, Doshisha University, 1-3 Tataramiyakodani, Kyo-Tanabe, Kyoto 610-0321, Japan. ' Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku Yokohama, Kanagawa 223-8522, Japan
Abstract: It is a key for the successes of data mining projects in practical situations to evaluate the obtained so many patterns as valuable knowledge effectively. In order to provide an effective support, we have been developing a rule evaluation support method based on the learning models of objective rule evaluation indices. In this paper, we report two improvements of this method and their evaluations. One is improved the learning algorithm selection in the proposed method by introducing a constructive meta-learning scheme. The other is improved the sorting efficiency of objective rule evaluation indices by combining them.
Keywords: data mining; post-processing; rule evaluation support; objective rule evaluation index; constructive meta-learning; PCA; principal component analysis; learning models; learning algorithm selection; sorting efficiency.
International Journal of Advanced Intelligence Paradigms, 2010 Vol.2 No.2/3, pp.180 - 197
Published online: 21 Dec 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article