Survey on Different Distance Metrics in K-Means Algorithm

Clustering is process of grouping similar data points or objects into same group. The k-means clustering is popular for cluster analysis in data mining. It is unsupervised because the points have no external classification. Distance metrics are used to find similar data objects on the basis of distance between data points and center points. so, distance metrics are very important element in k-means algorithm and play vital role in k means clustering. There are many distance metrics are available. In this paper we will do a review on k-means algorithm with different distance metrics.