PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

A Boolean Measure of Similarity
Martin Anthony and Peter Hammer
Discrete Applied Mathematics Volume 154, Number 6, 2006.

Abstract

We propose a way of measuring the similarity of a Boolean vector to a given set of Boolean vectors, motivated in part by certain data mining or machine learning problems. We relate the similarity measure to one based on Hamming distance and we develop from this some ways of quantifying the `quality' of a dataset.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:2746
Deposited By:Martin Anthony
Deposited On:22 November 2006