An Overview of Clustering Analysis Techniques Used in Data Mining
Clustering is the division of data into groups containing similar objects. It is used in fields such as pattern recognition, and machine learning. Searching for clusters involves unsupervised learning. Partitioning methods work by dividing a group of n elements into k clusters such that k is less than or equal to n and each cluster contains at least one element. Partitioning methods conduct one level partitioning on data sets. It iteratively improves the clusters by relocating objects from one group to a more relevant one. It continues this process until the clusters stabilize and no more migration of data from one cluster to another takes place.