Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
420139 | Discrete Applied Mathematics | 2012 | 12 Pages |
Abstract
Given linearly inseparable sets RR of red points and BB of blue points, we consider several measures of how far they are from being separable. Intuitively, given a potential separator (“classifier”), we measure its quality (“error”) according to how much work it would take to move the misclassified points across the classifier to yield separated sets. We consider several measures of work and provide algorithms to find linear classifiers that minimize the error under these different measures.
Keywords
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Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Boris Aronov, Delia Garijo, Yurai Núñez-Rodríguez, David Rappaport, Carlos Seara, Jorge Urrutia,