Combining Explicitness and Classifying Performance Via MIDOVA Lossless Representation for Qualitative Datasets

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Executive Summary

Basically, MIDOVA (Multidimensional Interaction Differential Of VAriability) lists the relevant combinations of K boolean variables in a datatable, giving rise to an appropriate expansion of the original set of variables, and well-fitted to a number of data mining tasks. A MIDOVUM takes into account the presence as well as the absence of items. The building of level-k itemsets starting from level-k-1 ones relies on the concept of residue, which entails the potential of an itemset to create higher-order non-trivial associations - unlike Apriori method, bound to count the sole presence of itemsets and exposed to the combinatorial explosion.

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