IDEAS home Printed from https://ideas.repec.org/p/una/unccee/wp0602.html
   My bibliography  Save this paper

Using Unlabeled Data to Improve Classification in the Naive Bayes Approach: Application to Web Searc

Author

Listed:
  • Stella M. Salvatierra

    (School of Economics and Business Administration, University of Navarra)

Abstract

This paper introduces a method to build a classifier based on labeled and unlabeled data. We set up the EM algorithm steps for the particular case of the naive Bayes approach and show empirical work for the restricted web page database. Original contributions includes the application of the EM algorithm to simulated data in order to see the behavior of the algorithm for different numbers of labeled and unlabeled data, and to study the effect of the sampling mechanism for the unlabeled data on the results.

Suggested Citation

  • Stella M. Salvatierra, 2002. "Using Unlabeled Data to Improve Classification in the Naive Bayes Approach: Application to Web Searc," Faculty Working Papers 06/02, School of Economics and Business Administration, University of Navarra.
    • Handle: RePEc:una:unccee:wp0602
    as

    Download full text from publisher

    File URL: http://www.unav.edu/documents/10174/6546776/1132239493_wp0602.pdf
    Download Restriction: no
    ---><---

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:una:unccee:wp0602. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: http://www.unav.edu/web/facultad-de-ciencias-economicas-y-empresariales .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.