DocumentCode :
1962349
Title :
The behavior of k-Means: An empirical study
Author :
Javed, Kashif ; Babri, Haroon A. ; Saeed, Mehreen
Author_Institution :
Dept. of Electr. Eng., Univ. of Eng. & Technol., Lahore
fYear :
2008
fDate :
25-26 March 2008
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, we study the behavior of the typical k-Means clustering algorithm by investigating the distributions of the final centroids, the sum-of-squares error and the iterations to convergence. This behavior is observed on two different synthetic data sets. It is found that when the clusters are well isolated from each other, the spread of the solutions found by k-Means algorithm indicates a much larger number of local minima as compared to the data set in which clusters overlap.
Keywords :
iterative methods; pattern clustering; statistical distributions; final centroid; k-means clustering algorithm; local minima; sum-of-squares error; synthetic data sets; Clustering algorithms; Computer errors; Computer science; Data analysis; Distributed computing; Euclidean distance; Image coding; Image segmentation; Iterative algorithms; Partitioning algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering, 2008. ICEE 2008. Second International Conference on
Conference_Location :
Lahore
Print_ISBN :
978-1-4244-2292-0
Electronic_ISBN :
978-1-4244-2293-7
Type :
conf
DOI :
10.1109/ICEE.2008.4553948
Filename :
4553948
Link To Document :
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