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Assessing the Performance of Classification Methods

Assessing the Performance of Classification Methods Summary A large number of measures have been developed for evaluating the performance of classification rules. Some of these have been developed to meet the practical requirements of specific applications, but many others—which here we call “classification accuracy” criteria—represent different ways of balancing the different kinds of misclassification which may be made. This paper reviews classification accuracy criteria. However, the literature is now so large and diverse that a comprehensive list, covering all the measures and their variants, would probably be impossible. Instead, this paper embeds such measures in general framework, spanning the possibilities, and draws attention to relationships between them. Important points to note are, firstly, that different performance measures, by definition, measure different aspects of performance; secondly, that one should therefore carefully choose a measure to match the objectives of one's study; and, thirdly, that empirical comparisons between instruments measuring different aspects are of limited value. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Statistical Review Wiley

Assessing the Performance of Classification Methods

International Statistical Review , Volume 80 (3) – Dec 1, 2012

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References (36)

Publisher
Wiley
Copyright
© 2012 The Author. International Statistical Review © 2012 International Statistical Institute
ISSN
0306-7734
eISSN
1751-5823
DOI
10.1111/j.1751-5823.2012.00183.x
Publisher site
See Article on Publisher Site

Abstract

Summary A large number of measures have been developed for evaluating the performance of classification rules. Some of these have been developed to meet the practical requirements of specific applications, but many others—which here we call “classification accuracy” criteria—represent different ways of balancing the different kinds of misclassification which may be made. This paper reviews classification accuracy criteria. However, the literature is now so large and diverse that a comprehensive list, covering all the measures and their variants, would probably be impossible. Instead, this paper embeds such measures in general framework, spanning the possibilities, and draws attention to relationships between them. Important points to note are, firstly, that different performance measures, by definition, measure different aspects of performance; secondly, that one should therefore carefully choose a measure to match the objectives of one's study; and, thirdly, that empirical comparisons between instruments measuring different aspects are of limited value.

Journal

International Statistical ReviewWiley

Published: Dec 1, 2012

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