Abstract

Clustering is a data mining (machine learning) technique used to place data elements into related groups without advance knowledge on the group definitions. In this paper the authors provides an in depth explanation of implementation of agglomerative and divisive clustering algorithms for various types of attributes. Database - the details of the victims of Tsunami in Thailand during the year 2004, was taken as the test data. The algorithms are implemented using Visual programming and the formation of the clusters and running time needed of the algorithms using different linkages (agglomerative) to different types of data are taken for analysis.

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