title: A new dataset evaluation method based on category overlap.
abstract: 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.
authors.affiliation: Department of Nanobiomedical Science, Dankook University, Cheonan 330-714, Republic of Korea. sejongoh@dankook.ac.kr
authors.forename: Sejong
authors.initials: S
authors.lastname: Oh
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D016571:Neural Networks, Computer