• DocumentCode
    2453291
  • Title

    Multi-Class Classification Using a New Sigmoid Loss Function for Minimum Classification Error (MCE)

  • Author

    Ratnagiri, M.V. ; Rabiner, L. ; Biing-Hwang Juang

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Rutgers Univ., Piscataway, NJ, USA
  • fYear
    2010
  • fDate
    12-14 Dec. 2010
  • Firstpage
    84
  • Lastpage
    89
  • Abstract
    A new loss function has been introduced for Minimum Classification Error, that approaches optimal Bayes´ risk and also gives an improvement in performance over standard MCE systems when evaluated on the Aurora connected digits database.
  • Keywords
    Bayes methods; pattern classification; Aurora connected digits database; minimum classification error; multi-class classification; optimal Bayes risk and; sigmoid loss function; Accuracy; Databases; Estimation; Hidden Markov models; Kernel; Loss measurement; Noise; Bayes Risk; Minimum Classification Error; Savage Loss; sigmoid loss;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications (ICMLA), 2010 Ninth International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4244-9211-4
  • Type

    conf

  • DOI
    10.1109/ICMLA.2010.20
  • Filename
    5708817
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2453291