Estimating the Costs Associated with Worthwhile Predictions of Poor Air Quality

  • Gavin C. Cawley
  • Stephen R. Dorling
  • Robert J. Foxall
  • Danilo P. Mandic
Conference paper


In this study we investigate the effect of varying the ratio of false-positive and false-negative misclassification costs on the sensitivity and selectivity of binary predictions of exceedences of atmospheric pollutants. This allows us to determine a window of values far this ratio far which it is worthwhile making definite rather than probabilistic predictions. The support vector machine provides a suitable statistical pattern recognition method for this work.


Support Vector Machine Training Pattern Misclassification Cost Support Vector Classification Radial Basis Func 
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Copyright information

© Springer-Verlag Wien 2001

Authors and Affiliations

  • Gavin C. Cawley
    • 1
  • Stephen R. Dorling
    • 2
  • Robert J. Foxall
    • 1
  • Danilo P. Mandic
    • 1
  1. 1.School of Information SystemsUniversity of East AngliaNorwich, NorfolkUK
  2. 2.School of Environmental SciencesUniversity of East AngliaNorwich, NorfolkUK

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