International Journal of Statistics and Applied Mathematics
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International Journal of Statistics and Applied Mathematics

2021, Vol. 6, Issue 5, Part B

Genetic algorithm approach to cluster analysis


Author(s): Nisha Sumbherwal and BK Hooda

Abstract: In this paper, performance of Genetic Algorithm based clustering method has been compared with conventional clustering methods that are K-means and Ward’s clustering methods. The cluster quality has been compared using three cluster validity indices that are Calinski-Harabasz, Dunn and Average Silhouette Width. The results showed that genetic algorithm based clustering method performed better than other clustering methods under all the three cluster validity measures.

Pages: 147-150 | Views: 17 | Downloads: 3

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How to cite this article:
Nisha Sumbherwal, BK Hooda. Genetic algorithm approach to cluster analysis. Int J Stat Appl Math 2021;6(5):147-150.
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