Comprehensive Review of K-Means Clustering Algorithms

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