ML Anthology

Application of Non Parametric Empirical Bayes Estimation to High Dimensional Classification

Eitan Greenshtein, Junyong Park
JMLR 2009 pp. 1687-1704
/jmlr/2009/greenshtein2009jmlr-application/

Abstract

We consider the problem of classification using high dimensional features' space. In a paper by Bickel and Levina (2004), it is recommended to use naive-Bayes classifiers, that is, to treat the features as if they are statistically independent.

PDF JMLR Semantic Scholar

Cite

Text

Greenshtein and Park. "Application of Non Parametric Empirical Bayes Estimation to High Dimensional Classification." Journal of Machine Learning Research, 2009.

Markdown

[Greenshtein and Park. "Application of Non Parametric Empirical Bayes Estimation to High Dimensional Classification." Journal of Machine Learning Research, 2009.](https://mlanthology.org/jmlr/2009/greenshtein2009jmlr-application/)

BibTeX

@article{greenshtein2009jmlr-application,
  title     = {{Application of Non Parametric Empirical Bayes Estimation to High Dimensional Classification}},
  author    = {Greenshtein, Eitan and Park, Junyong},
  journal   = {Journal of Machine Learning Research},
  year      = {2009},
  pages     = {1687-1704},
  volume    = {10},
  url       = {https://mlanthology.org/jmlr/2009/greenshtein2009jmlr-application/}
}