Discovery of Preliminary Centroids Using Improved K- Means Clustering Algorithm

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Provided by: International Journal of Computer Science and Information Technologies
Topic: Data Management
Format: PDF
The emergence of modern technology has enforced to collect the scientific data in a large quantity and those data are getting amassed in different databases. An organized analysis of data is very essential to obtain useful information from swiftly growing data repositories. Cluster analysis is one of the major data mining methods and the k-means clustering algorithm is widely used for many practical applications. But the original k-means algorithm is computationally expensive and the quality of the resulting clusters substantially relies on the choice of initial centroids.
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