期刊
COMPUTERS IN BIOLOGY AND MEDICINE
卷 41, 期 2, 页码 115-122出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compbiomed.2010.12.006
关键词
Feature; Feature selection; R-value; Dataset; Classification; Machine learning algorithm
类别
资金
- Ministry of Education, Science & Technology (MEST) [R31-2008-000-10069-0]
- Korea Science and Engineering Foundation (KOSEF)
- 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)
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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