A Boolean measure of similarity

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. Acknowledgements: Part of this work was carried out while Martin Anthony was visiting RUTCOR, Rutgers University. Martin Anthony’s work is supported in part by the IST Programme of the European Community, under the PASCAL Network of Excellence, IST2002-506778. The authors thank Alex Kogan, Ersoy Subasi, Mine Subasi, and Ben Veal for useful discussions.