Evaluating a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices

  • Hidenao Abe
  • Shusaku Tsumoto
  • Miho Ohsaki
  • Takahira Yamaguchi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3918)


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.


Training Dataset Human Expert Human Evaluation Rule Evaluation Objective Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hidenao Abe
    • 1
  • Shusaku Tsumoto
    • 1
  • Miho Ohsaki
    • 2
  • Takahira Yamaguchi
    • 3
  1. 1.Department of Medical InformaticsShimane University, School of MedicineShimaneJapan
  2. 2.Faculty of EngineeringDoshisha UniversityKyotoJapan
  3. 3.Faculty of Science and TechnologyKeio UniversityKanagawaJapan

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