Mining Determining Sets for Partially Defined Functions

Authors:
Dan A. Simovici;Dan Pletea;Rosanne Vetro
Affiliations:
Dept. of Comp. Science, Univ. of Massachusetts Boston, Massachusetts, USA 02125;Dept. of Comp. Science, Univ. of Massachusetts Boston, Massachusetts, USA 02125;Dept. of Comp. Science, Univ. of Massachusetts Boston, Massachusetts, USA 02125
Venue:
ICDM '09 Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects
Year:
2009

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Abstract

This paper describes an algorithm that determines the minimal sets of variables that determine the values of a discrete partial function. The Apriori-like algorithm is based on the dual hereditary property of determining sets. Experimental results are provided that demonstrate the efficiency of the algorithm for functions with up to 24 variables. The dependency of the number of minimal determining sets on the size of the specification of the partial function is also examined.