• DocumentCode
    1104354
  • Title

    On the Relationship Between Dependence Tree Classification Error and Bayes Error Rate

  • Author

    Balagani, Kiran S. ; Phoha, Vir V.

  • Author_Institution
    Louisiana Tech. Univ., Ruston
  • Volume
    29
  • Issue
    10
  • fYear
    2007
  • Firstpage
    1866
  • Lastpage
    1868
  • Abstract
    Wong and Poon (1989) showed that Chow and Liu´s tree dependence approximation can be derived by minimizing an upper bound of the Bayes error rate. Wong and Poon´s result was obtained by expanding the conditional entropy H(omega|X). We derive the correct expansion of H(omega|X) and present its implication.
  • Keywords
    Bayes methods; pattern classification; trees (mathematics); Bayes error rate; tree classification error; tree dependence approximation; Classification tree analysis; Entropy; Equations; Error analysis; Mutual information; Probability distribution; Random variables; State estimation; Upper bound; bayes error rate; classification; dependence tree approximation; entropy; mutual information; Algorithms; Artificial Intelligence; Bayes Theorem; Computer Simulation; Data Interpretation, Statistical; Models, Statistical; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Statistics as Topic;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2007.1184
  • Filename
    4293215
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1104354