Implementation of Different Clustering Algorithms/Farklı Sınıflandırma Algoritmalarının Uygulamaları

Year 2018, Volume: 2 Issue: 1, 49 - 66, 01.07.2018

Amna Mohamed M. Aburas Wamidh Mazher Osman Nuri Uçan , Oğuz Bayat

Abstract

Abstract

Spectral clustering is developed for both normalized and unnormalized methods. However, selecting between the

two methods is not established in the GUI (Graphical User Interface) yet . In this paper , we implement different

clustering algorithms using GUI-MATLAB, then, the clustering by these three methods, is compared for similar pairs

of datasets. Our model is employing such three different clustering methods which are spectral, hierarchical

and density based methods, then employing different geometrical, multi-range, and multi-level similar datasets

pairs of graph for clustering. As result, the above three clustering algorithms are experimented for different environments

which are (geometrical, multi-range and multi-level). The simulation result shows the clustering of

these pairs of geometrical datasets which are: Concentric circles, Semi-circles, and Aggregation. Accordingly, the

spectral algorithm has superior clustering in case of big datasets more than 2000 pairs points and range more

than 500 levels among datasets

Keywords

Clustering, K-means, Spectral method, Laplace, Eigenvector, GUI

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