Abstract
We present an evaluation of a rule evaluation support method for post-processing of mined results with rule evaluation models based on objective indices in this paper. To reduce the costs of rule evaluation task, which is one of the key procedures in data mining post-processing, 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. Then we have evaluated performances of learning algorithms for constructing rule evaluation models on the meningitis data mining as an actual problem, and ten rule sets from the ten kinds of UCI datasets as an article problem. With these results, we show the availability of our rule evaluation support method.
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Abe, H., Tsumoto, S., Ohsaki, M., Yamaguchi, T. (2006). Evaluating Learning Models for a Rule Evaluation Support Method Based on Objective Indices. In: Greco, S., et al. Rough Sets and Current Trends in Computing. RSCTC 2006. Lecture Notes in Computer Science(), vol 4259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11908029_71
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DOI: https://doi.org/10.1007/11908029_71
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