Research Paper | Computer Science & Engineering | China | Volume 7 Issue 4, April 2018
Improvement of k-Means Clustering Algorithm by GA
Khamis H Haroun | Wu Zhifeng
Abstract: As known that K-means algorithm is the one of the common and popular technique for solving clustering problems. In fact, there are many k-means algorithms for solving the clustering problem such as Lloyds k-means clustering algorithm, hierarchical k-means algorithm, also Grid based k-means algorithm etc. In the classical k-means algorithm the selected value of k must be confirmed first. So, the resulting clusters mainly depends on the selection of the initial centroids. It is not simple job to select the accurately value of k or to know exactly number of clusters for the given data set. So that in this paper propose new algorithm that called improvement of k-means clustering algorithm by GA that algorithm will be able to automatic find the best initial centers and appropriation of clusters according to the given data set.
Keywords: Clustering, K-means, Cluster centroid, Genetic algorithm
Edition: Volume 7 Issue 4, April 2018,
Pages: 1429 - 1435
How to Cite this Article?
Khamis H Haroun, Wu Zhifeng, "Improvement of k-Means Clustering Algorithm by GA", International Journal of Science and Research (IJSR), Volume 7 Issue 4, April 2018, pp. 1429-1435, https://www.ijsr.net/get_abstract.php?paper_id=ART20181981
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