Notes on the H-measure of classifier performance

D. J. Hand () and C. Anagnostopoulos
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D. J. Hand: Imperial College
C. Anagnostopoulos: Imperial College

Advances in Data Analysis and Classification, 2023, vol. 17, issue 1, No 6, 109-124

Abstract: Abstract The H-measure is a classifier performance measure which takes into account the context of application without requiring a rigid value of relative misclassification costs to be set. Since its introduction in 2009 it has become widely adopted. This paper answers various queries which users have raised since its introduction, including questions about its interpretation, the choice of a weighting function, whether it is strictly proper, its coherence, and relates the measure to other work.

Keywords: Classification; Machine learning; Classifier performance; Evaluation; Assessment; Area under the curve; Strictly proper scoring rules; 62-02; 62H30; 68-02 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11634-021-00490-3

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