Abstract
In this paper, we present an evaluation of 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 issues in a data mining process. However, it is difficult for human experts to evaluate many thousands of rules from a large dataset with noises completely. To reduce the costs of rule evaluation task, we have developed the rule evaluation support method with rule evaluation models, which are obtained with objective indices of mined classification rules and evaluations of a human expert for each rule. To evaluate performances of learning algorithms for constructing 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 on four rulesets from the four kinds of UCI datasets.
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Abe, H., Tsumoto, S., Ohsaki, M., Yamaguchi, T. (2006). Evaluating a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices. In: Ng, WK., Kitsuregawa, M., Li, J., Chang, K. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2006. Lecture Notes in Computer Science(), vol 3918. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11731139_60
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DOI: https://doi.org/10.1007/11731139_60
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