Normalization based K-means Data Analysis Algorithm

Navdeep Kaur, Bhavika Jagga, Dinesh Gupta


Data mining is analysis step to knowledge discovery in the database process. It is the process of extraction knowledge from large databases. Clustering is a process of partitioning a set of data (or objects) into a set of meaningful sub-classes, called clusters. Used either as a stand-alone tool to get insight into datadistribution or as a preprocessing step for other algorithms. K-means is a good clustering technique. With the proposed algorithm, normalization of data prior to clustering. Then a efficient algorithm used for clustering which is better than simple k-means algorithm.

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