Comprehensive Review of K-Means Clustering Algorithms

This paper presents a comprehensive review of existing techniques k-means clustering algorithms made at various times. The algorithm is aimed partitioning objects or points to be analyzed into well separated clusters. There are different for such as traditional algorithm, standard basic and the conventional this perhaps most widely used versions algorithms. These uses Euclidean distance its metric minimum rule approach by assigning each data (objects) closest centroids.