Applications of Cluster Analysis - Aruna, T (International Journal of Computer Sciences and Engineering, 2025)
Clustering is the process of grouping the data into classes or clusters, so those objects with in a cluster have high similarity in comparison to one another but are very dissimilar to objects in other clusters. Dissimilarities are assessed based on attribute values describing the objects. Clustering has its roots in many areas like data mining, statistics, biology and machine learning. We examine several clustering techniques organized into the following categories partitioning methods, hierarchical method, density based method, grid- based method, model-based method, frequent pattern based method and constraint clustering.