Comparative Study of Initial Centroid based K-Mode Algorithm
| Author(s) | : | Manisha Goyal, Shruti Aggarwal |
| Institution | : | Research Scholar, Department of Computer Science and Engineering, Sri Guru Granth Sahib World University, Fatehgarh Sahib |
| Published In | : | Vol. 4, Issue 9 — September 2017 |
| Page No. | : | 171-177 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Clustering is one of the techniques of the data mining, which defines classes and put the objects into onegroup having similar properties and objects having dissimilar properties into another group. An extension of the KMeans Algorithm, K-Mode Algorithm, is partitioning based clustering algorithm but it does not guarantee for the optimalsolution. In this paper, there is the comparative analysis of Ini_Distance and Ini_Entropy Algorithm with Cao’s methods,WK-Mode with Chan’s Algorithm, Harmonic K-Mode with K-Mode and EC K-Mode Algorithm on real datasets. Thesealgorithms are based on the selection of initial centroids in which the clustering accuracy is improved. The algorithmsdiscussed in this study can be improved further by other better optimization techniques through research made in thisfield.
Manisha Goyal, Shruti Aggarwal, “Comparative Study of Initial Centroid based K-Mode Algorithm”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 9, pp. 171-177, September 2017.
