Centre for Discrete and Applicable Mathematics
	CDAM Research Report, LSE-CDAM-2005-06 March 2005

Abstract

Here we investigate properties of a measure of similarity between a binary vector and a set of binary vectors that we believe may be useful for classification of medical data. We present combinatorial and asymptotic properties, and some results useful for binary classification. We show that if our underlying function is assumed to be a bounded term DNF, then our hypothesis function will correctly classify any example with large similarity measure.

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Last modified: 9th March 2005