ML Anthology

Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval

David D. Lewis
ECML-PKDD 1998 pp. 4-15
doi:10.1007/BFB0026666 /ecmlpkdd/1998/lewis1998ecml-naive/

Abstract

The naive Bayes classifier, currently experiencing a renaissance ] in machine learning, has long been a core technique in information retrieval. We review some of the variations of naive Bayes models used for text retrieval and classification, focusing on the distributional assumptions made about word occurrences in documents.

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Cite

Text

Lewis. "Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval." European Conference on Machine Learning, 1998. doi:10.1007/BFB0026666

Markdown

[Lewis. "Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval." European Conference on Machine Learning, 1998.](https://mlanthology.org/ecmlpkdd/1998/lewis1998ecml-naive/) doi:10.1007/BFB0026666

BibTeX

@inproceedings{lewis1998ecml-naive,
  title     = {{Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval}},
  author    = {Lewis, David D.},
  booktitle = {European Conference on Machine Learning},
  year      = {1998},
  pages     = {4-15},
  doi       = {10.1007/BFB0026666},
  url       = {https://mlanthology.org/ecmlpkdd/1998/lewis1998ecml-naive/}
}