Performance Analysis of Clustering Techniques to Normal and Uniform Distribution of Data Points
نویسنده
چکیده
Clustering technique is one of the most important research areas in the field of data mining. This paper proposes an improved K-Means clustering algorithm form partition based clustering algorithms. It determines the initial centroid of the cluster and gives more efficient performance and reduces the time complexity of the large data sets. The data set used here is banking data. Fuzzy C-Means clustering algorithm also implemented since it produces the soft clusters. Finally the proposed algorithm is compared and analyzed for the Normal and Uniform distribution of data point with KMeans, Fuzzy C-Means and K-Medoids. The computational complexity and performance is showed much better with improved K-Means algorithm. Keywords— Clustering, K-Means, Fuzzy C-Means, KMediods, Normal and Uniform distribution
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