Fuzzy Clustering Data Given on the Ordinal Scale Based on Membership and Likelihood Functions Sharing
Machine Learning
2017-02-07 v1
Abstract
A task of clustering data given in the ordinal scale under conditions of overlapping clusters has been considered. It's proposed to use an approach based on memberhsip and likelihood functions sharing. A number of performed experiments proved effectiveness of the proposed method. The proposed method is characterized by robustness to outliers due to a way of ordering values while constructing membership functions.
Cite
@article{arxiv.1702.01200,
title = {Fuzzy Clustering Data Given on the Ordinal Scale Based on Membership and Likelihood Functions Sharing},
author = {Zhengbing Hu and Yevgeniy V. Bodyanskiy and Oleksii K. Tyshchenko and Viktoriia O. Samitova},
journal= {arXiv preprint arXiv:1702.01200},
year = {2017}
}
Comments
International Journal of Intelligent Systems and Applications(IJISA), Vol. 9, No. 2, February 2017