Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
421471 | Discrete Applied Mathematics | 2006 | 5 Pages |
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Martin Anthony, Peter L. Hammer,