PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Properties of a binary similarity measure
Ben Veal
(2005) Technical Report. CDAM Research Reports Series, London, UK.

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.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Monograph (Technical Report)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:2027
Deposited By:Ben Veal
Deposited On:15 January 2006