A Survey Paper on Modified Approach for Kmeans Algorithm
Journal Title: International journal of Emerging Trends in Science and Technology - Year 2016, Vol 3, Issue 2
Abstract
Kmeans type clustering aims at partitioning a data set into clusters such that the objects in a cluster are compact and the objects in different clusters are well separated. However, most kmeans-type clustering algorithms rely on only intracluster compactness while overlooking intercluster separation. A series of new clustering algorithms by extending the existing kmeans-type algorithms is proposed by integrating both intracluster compactness and intercluster separation. First, a set of new objective functions for clustering is developed. Based on these objective functions, the corresponding updating rules for the algorithms are then derived analytically. The new algorithm with new objective function to solve the problem of intracluster compactness and intercluster separation has been proposed. Proposed FCS based algorithm works simultaneously on both i.e. intracluster compactness and intercluster separation and it will give a better performance over existing Kmeans
Authors and Affiliations
Amruta S. Suryavanshi
Keywords
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