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    Grid-based supervised clustering algorithm using greedy and gradient descent methods to build clusters 

    Pornpimol Bungkomkhun; Surapong Auwatanamongkol, advisor (National Institute of Development Administration, 2012)

    Clustering analysis is one of the primary methods of data mining tasks with the objective to understand the natural grouping (or structure) of data objects in a dataset. The clustering tasks aim to segment the entire data set into relatively homogenous subgroups or clusters where the similarities of the data objects within clusters are maximized and the similarities of data objects belonging to different clusters are minimized. For supervised clustering, not only attribute variables of data objects but also the class variable of data objects take ...