A SURVEY ON ENHANCING AGGLOMERATIVE HIERARCHICAL TECHNIQUES
Keywords:
Data Mining, Hierarchical Clustering Algorithm, BIRCH Algorithm, CURE Algorithm, ROCK AlgorithmAbstract
Clustering algorithms classify data points into meaningful groups based on similarity. Clustering is used in
biological and medical applications, computer vision, robotics, and geographical data. A hierarchical clustering is
working on grouping of data objects into tree of clusters. This paper is used on the hierarchical clustering for large
numerical datasets. This approach is used to clustering starts with each observation as its own cluster and then
continually groups the observations into increasing larger groups. Birch does not perform well because of radius or
diameter to control the boundary of a cluster. Each node in a CF tree can hold only a limited number of entries because
of its size. BIRCH suffers from identifying only convex or spherical shapes of uniform size.