The Tangent Classifier

José R. Berrendero and Javier Cárcamo

The American Statistician, 2012, vol. 66, issue 3, 185-194

Abstract: Given a classifier, we describe a general method to construct a simple linear classification rule. This rule, called the tangent classifier , is obtained by computing the tangent hyperplane to the separation boundary of the groups (generated by the initial classifier) at a certain point. When applied to a quadratic region, the tangent classifier has a neat closed-form expression. We discuss various examples and the application of this new linear classifier in two situations under which standard rules may fail: when there is a fraction of outliers in the training sample and when the dimension of the data is large in comparison with the sample size.

Date: 2012
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DOI: 10.1080/00031305.2012.710511

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