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Soft Computing
Published in:

19-07-2018 | Methodologies and Application

A string grammar possibilistic-fuzzy C-medians

Authors: Atcharin Klomsae, Sansanee Auephanwiriyakul, Nipon Theera-Umpon

Published in: Soft Computing | Issue 17/2019

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Abstract

In the context of syntactic pattern recognition, we adopt the fuzzy clustering approach to classify the syntactic pattern. A syntactic pattern can be described using a string grammar. Fuzzy clustering has been shown to have better performance than hard clustering. Previously, to improve the string grammar hard C-means, we introduced a string grammar fuzzy C-medians and string grammar fuzzy-possibilistic C-medians algorithm. However, both algorithms have their own problem. Thus, in this paper, we develop a string grammar possibilistic-fuzzy C-medians algorithm. The experiments on four real data sets show that string grammar possibilistic-fuzzy C-medians has better performance than string grammar hard C-means, string grammar fuzzy C-medians, and string grammar fuzzy-possibilistic C-medians. We claim that the proposed string grammar possibilistic-fuzzy C-medians is better than the other string grammar clustering algorithms.
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Metadata
Title
A string grammar possibilistic-fuzzy C-medians
Authors
Atcharin Klomsae
Sansanee Auephanwiriyakul
Nipon Theera-Umpon
Publication date
19-07-2018
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 17/2019
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-3392-6

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