Compatibility of Clique Clustering Algorithm with Dimensionality Reduction

Authors

Ug ̆ur Madran, College of Engineering and Technology, American University of the Middle East, 54200 Egaila, KuwaitFollow
Duygu Soyog ̆lu, College of Engineering and Technology, American University of the Middle East, 54200 Egaila, KuwaitFollow

Author Country (or Countries)

Kuwait

Abstract

In our previous work, we introduced a clustering algorithm based on clique formation. Cliques, the obtained clusters, are constructed by choosing the most dense complete subgraphs by using similarity values between instances. The clique algorithm successfully reduces the number of instances in a data set without substantially changing the accuracy rate. In this current work, we focused on reducing the number of features. For this purpose, the effect of the clique clustering algorithm on dimensionality reduction has been analyzed. We propose a novel algorithm for support vector machine classification by combining these two techniques and applying different strategies by differentiating the clique structures. The results obtained from well known data sets confirm the compatibility of clique clustering algorithm with dimensionality reduction.

Digital Object Identifier (DOI)

http://dx.doi.org/10.18576/amis/170510

Recommended Citation

̆ur Madran, Ug and Soyog ̆lu, Duygu (2023) "Compatibility of Clique Clustering Algorithm with Dimensionality Reduction," Applied Mathematics & Information Sciences: Vol. 17: Iss. 5, Article 10.
DOI: http://dx.doi.org/10.18576/amis/170510
Available at: https://digitalcommons.aaru.edu.jo/amis/vol17/iss5/10