Investigation of the performance of some clustering algorithms

Investigation of the performance of some clustering algorithms

Abstract In this dissertation, we investigate the performance of K-means, SOM and EM clustering algorithms based on UCI datasets. Tests are performed using three datasets. Two measures which are mostly used for comparing the performance of clustering algorithms. The first concerns the quality of clu...

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Bibliographic Details
Main Author: Tin Zar Kyaw.
Other Authors: School of Electrical and Electronic Engineering
Format: Theses and Dissertations
Published: 2008
Subjects:
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:http://hdl.handle.net/10356/3602
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Institution: Nanyang Technological University
Description
Summary:Abstract In this dissertation, we investigate the performance of K-means, SOM and EM clustering algorithms based on UCI datasets. Tests are performed using three datasets. Two measures which are mostly used for comparing the performance of clustering algorithms. The first concerns the quality of clustering algorithms. The second measure deals with the accuracy of clustering results. The results of the experiments suggest that Expectation Maximization (EM) is more robust to outliners than K-means and SOM.

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