  K-means is an effective clustering technique used to separate similar data
into groups based on initial centroids of clusters. In this paper,
Normalization based K-means clustering algorithm(N-K means) is proposed.
Proposed N-K means clustering algorithm applies normalization prior to
clustering on the available data as well as the proposed approach calculates
initial centroids based on weights. Experimental results prove the betterment
of proposed N-K means clustering algorithm over existing K-means clustering
algorithm in terms of complexity and overall performance.
