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Evaluating Learning Algorithms to Support Human Rule Evaluation Based on Objective Rule Evaluation Indices

Authors:

H Abe ,

Dept of Medical Informatics, Shimane University, School of Medicine, 89-1 Enya-cho Izumo Shimane, 6938501, Japan
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S Tsumoto,

Dept of Medical Informatics, Shimane University, School of Medicine, 89-1 Enya-cho Izumo Shimane, 6938501, Japan
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M Ohsaki,

Faculty of Engineering, Doshisha University, 1-3 Tataramiyakodani Kyo-Tanabe Kyoto, 6100321, Japan
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T Yamaguchi

Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi Kohoku-ku Yokohama Kanagawa, 2238522, Japan
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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 noise. To reduce the costs in such rule evaluation task, we have developed a rule evaluation support method with rule evaluation models that learn from a dataset. This dataset comprises objective indices for mined classification rules and evaluation by a human expert for each rule. To evaluate performances of learning algorithms for constructing the rule evaluation models, we have done a case study on the meningitis data mining as an actual problem. Furthermore, we have also evaluated our method with ten rule sets obtained from ten UCI datasets. With regard to these results, we show the availability of our rule evaluation support method for human experts.
DOI: http://doi.org/10.2481/dsj.6.S285
How to Cite: Abe, H. et al., (2007). Evaluating Learning Algorithms to Support Human Rule Evaluation Based on Objective Rule Evaluation Indices. Data Science Journal. 6, pp.S285–S296. DOI: http://doi.org/10.2481/dsj.6.S285
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Published on 17 May 2007.
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