Coefficient of variation based decision tree for fuzzy classification

0Citations
Citations of this article
1Readers
Mendeley users who have this article in their library.
Get full text

Abstract

This paper considers a decision system with a fuzzy decision attribute (with finite set of values) to account for uncertainty. A novel fuzzy classification approach using a class of decision trees is developed. A decision tree is constructed for each decision category using Coefficient of Variation Gain as the attribute selection measure. A metric based on Residual Sum of Squares (RSS) to compare the fuzzy classifier is presented. The methodology of constructing the classifier and its performance aspects are presented.

Cite

CITATION STYLE

APA

Hima Bindu, K., & Raghavendra Rao, C. (2015). Coefficient of variation based decision tree for fuzzy classification. In Advances in Intelligent Systems and Computing (Vol. 415, pp. 139–149). Springer Verlag. https://doi.org/10.1007/978-3-319-27212-2_11

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free