4.7 Article

A new dataset evaluation method based on category overlap

Journal

COMPUTERS IN BIOLOGY AND MEDICINE
Volume 41, Issue 2, Pages 115-122

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2010.12.006

Keywords

Feature; Feature selection; R-value; Dataset; Classification; Machine learning algorithm

Funding

  1. Ministry of Education, Science & Technology (MEST) [R31-2008-000-10069-0]
  2. Korea Science and Engineering Foundation (KOSEF)
  3. Ministry of Education, Science & Technology (MoST), Republic of Korea [R31-2008-000-10069-0] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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The quality of dataset has a profound effect on classification accuracy, and there is a clear need for some method to evaluate this quality. In this paper, we propose a new dataset evaluation method using the R-value measure. This proposed method is based on the ratio of overlapping areas among categories in a dataset. A high R-value for a dataset indicates that the dataset contains wide overlapping areas among its categories, and classification accuracy on the dataset may become low. We can use the R-value measure to understand the characteristics of a dataset, the feature selection process, and the proper design of new classifiers. (C) 2010 Elsevier Ltd. All rights reserved.

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