Dataset Analysis Using Membership-Deviation Graph
Itgel Bayarsaikhan, Jimin Lee, Sejong Oh · Zenodo (CERN European Organization for Nuclear Research) · 2010
Classification is one of the primary themes in computational biology. The accuracy of classification strongly depends on quality of a dataset, and we need some method to evaluate this quality. In this paper, we propose a new graphical analysis method using 'Membership-Deviation Graph (MDG)' for analyzing quality of a dataset. MDG represents degree of membership and deviations for instances of a class in the dataset. The result of MDG analysis is used for understanding specific feature and for selecting best feature for classification.