(Publisher of Peer Reviewed Open Access Journals)

International Journal of Advanced Computer Research (IJACR)

ISSN (Print):2249-7277    ISSN (Online):2277-7970
Volume-11 Issue-57 November-2021
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Paper Title : KMK based hybrid approach for the performance estimation in case of diabetes data
Author Name : Yasir Minhaj Khan and Animesh Kumar Dubey
Abstract :

In this paper k-means clustering algorithm has been used with k-points (KMK) selection. It has been applied on the PIMA Indian diabetes dataset. It has been used for distance estimation, centroid selection, effect of data size variations and for the analysis of the complete record. The cluster section has been found to be improved based on k-point selection. It has been used for the assignment of initial centroid. The results indicate that the KMK algorithm is capable in the improvement of centroid selection and distance measures in the assignments of data points. It is due to the better centroid selection mechanism by k-points selection based on the weight measures from the selected dataset. So, the obtained clusters are better in comparison to k-means.

Keywords : K-means, KMK, PIMA, Similarity score, Centroid estimation.
Cite this article : Khan YM, Dubey AK. KMK based hybrid approach for the performance estimation in case of diabetes data. International Journal of Advanced Computer Research. 2021; 11(57):116-121. DOI:10.19101/IJACR.2021.1152043.
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