Simple tiered classifiers

Peter Hall, Yingcun Xia and Jing-Hao Xue

Biometrika, 2013, vol. 100, issue 2, 431-445

Abstract: In this paper we propose simple, general tiered classifiers for relatively complex data. Empirical studies on real and simulated data show that three two-tier classifiers, which are respective extensions of linear discriminant analysis, linear logistic regression and support vector machines, can reduce noticeably the relatively high misclassification error of their original single-tier counterparts, without significantly increasing computational labour. Copyright 2013, Oxford University Press.

Date: 2013
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