ML Anthology

Bayesian Hypothesis Testing in Machine Learning

Giorgio Corani, Alessio Benavoli, Francesca Mangili, Marco Zaffalon
ECML-PKDD 2015 pp. 199-202
doi:10.1007/978-3-319-23461-8_13 /ecmlpkdd/2015/corani2015ecmlpkdd-bayesian/

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.

PDF ECML-PKDD Semantic Scholar

Cite

Text

Corani et al. "Bayesian Hypothesis Testing in Machine Learning." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2015. doi:10.1007/978-3-319-23461-8_13

Markdown

[Corani et al. "Bayesian Hypothesis Testing in Machine Learning." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2015.](https://mlanthology.org/ecmlpkdd/2015/corani2015ecmlpkdd-bayesian/) doi:10.1007/978-3-319-23461-8_13

BibTeX

@inproceedings{corani2015ecmlpkdd-bayesian,
  title     = {{Bayesian Hypothesis Testing in Machine Learning}},
  author    = {Corani, Giorgio and Benavoli, Alessio and Mangili, Francesca and Zaffalon, Marco},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  year      = {2015},
  pages     = {199-202},
  doi       = {10.1007/978-3-319-23461-8_13},
  url       = {https://mlanthology.org/ecmlpkdd/2015/corani2015ecmlpkdd-bayesian/}
}