Between AUC based and error rate based learning

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Based on an earlier solution to optimize an approximated area under the ROC Curve (AUC) for binary pattern classification in [1], this paper investigates into the relationship between AUC and several error rate based classifiers. Via a generalized framework of translated scalingspace, we find that the AUC based classifier can be related to a total-error-rate (TER) classifier, an Equal Error Rate (EER) formulation, and a least-squares-error (LSE) estimator, each under a specific setting of the translated scaling-space framework. Several potential applications of the generalized framework are subsequently discussed.

Original languageEnglish
Title of host publication2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008
Pages2116-2120
Number of pages5
DOIs
Publication statusPublished - 2008
Event2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 - Singapore, Singapore
Duration: 2008 Jun 32008 Jun 5

Publication series

Name2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008

Other

Other2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008
CountrySingapore
CitySingapore
Period08/6/308/6/5

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering

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  • Cite this

    Toh, K. A. (2008). Between AUC based and error rate based learning. In 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 (pp. 2116-2120). [4582893] (2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008). https://doi.org/10.1109/ICIEA.2008.4582893