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Classification, Clustering, and Data Mining Applications
Association rules for objects with quantitative attributes require the discretization of these attributes to limit the size of the search space. As each such discretization might collapse attribute levels that need to be distinguished for finding association rules, optimal discretization strategies are of interest. In 1996 Srikant and Agrawal formulated an information loss measure called measure of partial completeness and claimed that equidepth partitioning (i.e. discretization based on basedoi:10.1007/978-3-642-17103-1_28 fatcat:tkqg6oapifae7fjh5cwbbjb3da