Comparative Analysis of BIRCH and CURE Hierarchical Clustering Algorithm using WEKA 3.6.9

Hierarchical clustering is the process of forming a maximal collection of subsets of objects (called clusters), with the property that any two clusters are either disjoint or nested. Hierarchical clustering combine data objects into clusters, those clusters into larger clusters, and so forth, creates a hierarchy of clusters, which may represent a tree structure called a dendrogram, in which the root of the tree consists of a single cluster containing all observations, and the leaves correspond to individual observations. BIRCH and CURE are two integrated hierarchical clustering algorithm.

Provided by: Creative Commons Topic: Data Management Date Added: Feb 2014 Format: PDF

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