Joint European Conference on Machine Learning and Knowledge Discovery in Databases

ECML PKDD 2015: Machine Learning and Knowledge Discovery in Databases pp 199-202

Bayesian Hypothesis Testing in Machine Learning

  • Giorgio Corani
  • Alessio Benavoli
  • Francesca Mangili
  • Marco Zaffalon
Conference paper

DOI: 10.1007/978-3-319-23461-8_13

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9286)
Cite this paper as:
Corani G., Benavoli A., Mangili F., Zaffalon M. (2015) Bayesian Hypothesis Testing in Machine Learning. In: Bifet A. et al. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2015. Lecture Notes in Computer Science, vol 9286. Springer, Cham

Abstract

Most hypothesis testing in machine learning is done using the frequentist null-hypothesis significance test, which has severe drawbacks. We review recent Bayesian tests which overcome the drawbacks of the frequentist ones.

Keywords

Bayesian hypothesis testing Null hypothesis significance testing 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Giorgio Corani
    • 1
  • Alessio Benavoli
    • 1
  • Francesca Mangili
    • 1
  • Marco Zaffalon
    • 1
  1. 1.Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), USI - SUPSIMannoSwitzerland

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