K-Means Clustering in Spatial Data Mining using Weka Interface
Ritu Sharma, M. Afshar Alam, Anita Rani · International Conference on Advances in Communication and Computing Technologies · 2012
Clustering techniques have a wide use and importance nowadays and this importance tends to increase as the amount of data grows. K-means is a simple technique for clustering analysis. Its aim is to find the best division of n entities into k groups (called clusters), so that total distance between the group's members and corresponding centroid, irrespective of the group is minimized. Each entity belongs to the cluster with the nearest mean. It results into a