Anupama Chadha

Work place: Faculty of Computer Applications, MRIU, Faridabad, India



Research Interests: Data Mining, Data Structures and Algorithms


Ms. Anupama Chadha is a research scholar in Department of Computer Science and Engineering, Manav Rachna International University. Her area of interest include Data Mining, Software Engineering.

Author Articles
Extension of K-Modes Algorithm for Generating Clusters Automatically

By Anupama Chadha Suresh Kumar

DOI:, Pub. Date: 8 Mar. 2016

K-Modes is an eminent algorithm for clustering data set with categorical attributes. This algorithm is famous for its simplicity and speed. The K-Modes is an extension of the K-Means algorithm for categorical data. Since K-Modes is used for categorical data so 'Simple Matching Dissimilarity' measure is used instead of Euclidean distance and the 'Modes' of clusters are used instead of 'Means'. However, one major limitation of this algorithm is dependency on prior input of number of clusters K, and sometimes it becomes practically impossible to correctly estimate the optimum number of clusters in advance. In this paper we have proposed an algorithm which will overcome this limitation while maintaining the simplicity of K-Modes algorithm.

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