Cookies?
Library Header Image
LSE Research Online LSE Library Services

Using a similarity measure for credible classification

Anthony, Martin and Hammer, P. L. and Subasi, E. and Subasi, M. (2005) Using a similarity measure for credible classification. CDAM research report series, CDAM-LSE-2005-22. Centre for Discrete and Applicable Mathematics, London School of Economics and Political Science, London, UK.

Full text not available from this repository.

Abstract

This paper concerns classification by Boolean functions. We investigate the classification accuracy obtained by standard classification techniques on unseen points (elements of the domain, {0, 1}n, for some n) that are similar, in particular senses, to the points that have been observed as training obser- vations. Explicitly, we use a new measure of how similar a point x ∈ {0, 1}n is to a set of such points to restrict the domain of points on which we offer a classification. For points sufficiently dissimilar, no classification is given. We report on experimental results which indicate that the classification ac- curacies obtained on the resulting restricted domains are better than those obtained without restriction. These experiments involve a number of standard data-sets and classification techniques. We also compare the classification ac- curacies with those obtained by restricting the domain on which classification is given by using the Hamming distance.

Item Type: Monograph (Report)
Official URL: http://www.cdam.lse.ac.uk
Additional Information: © 2005 the authors
Subjects: Q Science > QA Mathematics
Sets: Departments > Mathematics
Date Deposited: 23 Oct 2008 09:43
Last Modified: 08 Nov 2012 16:09
URI: http://eprints.lse.ac.uk/id/eprint/13927

Actions (login required)

View Item View Item