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 …

Clustering technique is mainly focus on pattern recognition for further organizational design
analysis which finds groups of data objects such that objects in a group are similar to one …

K-means clustering algorithm and one of its enhancements are studied in this paper.
Clustering is the classification of objects into different groups, or more precisely, the …

The cluster number is not generally set by K-means clustering algorithm beforehand, and
artificial initial clustering number easily leads to the problem of unstable clustering results. A …

The famous K-means clustering algorithm is sensitive to the selection of the initial centroids
and may converge to a local minimum of the criterion function value. A new algorithm for …