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A fuzzified BRAIN algorithm for learning DNF from incomplete data


Abstract


Aim of this paper is to address the problem of learning Boolean functions from training data with missing values. We present an extension of the BRAIN algorithm, called U-BRAIN (Uncertainty-managing Batch Relevance-based Artificial INtelligence), conceived for learning DNF Boolean formulas from partial truth tables, possibly with uncertain values or missing bits.

DOI Code: 10.1285/i20705948v5n2p256

Keywords: Boolean function; DNF; Learning algorithm; Missing Values.

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