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Sparse Bayesian Classifiers for Text Categorization (2003)  (Make Corrections)  (1 citation)
Susana Eyheramendy, Alexander Genkin, Wen-Hua Ju, David D. Lewis, David Madagin



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Abstract: This paper empirically compares the performance of di#erent Bayesian models for text categorization. In particular we examine so-called "sparse" Bayesian models that explicitly favor simplicity. We present empirical evidence that these models retain good predictive capabilities while o#ering significant computational advantages. (Update)

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Eyheramendy, S., Genkin, A., Ju, W., Lewis, D. D., and Madigan, D. (2003). Sparse bayesian classifiers for text categorization. Technical report, Department of Statistics, Rutgers University. http://citeseer.ist.psu.edu/article/eyheramendy03sparse.html   More

@misc{ eyheramendy03sparse,
  author = "S. Eyheramendy and A. Genkin and W. Ju and D. Lewis and D. Madigan",
  title = "Sparse bayesian classifiers for text categorization",
  text = "Eyheramendy, S., Genkin, A., Ju, W., Lewis, D. D., and Madigan, D. (2003).
    Sparse bayesian classifiers for text categorization. Technical report, Department
    of Statistics, Rutgers University.",
  year = "2003",
  url = "citeseer.ist.psu.edu/article/eyheramendy03sparse.html" }
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