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    Efficient Cross-validation of the complete Two stages in KFD Classifier Formulation

    Access Status
    Fulltext not available
    Authors
    An, Senjian
    Liu, Wan-Quan
    Venkatesh, Svetha
    Date
    2006
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    An, S. and Liu, W. and Venkatesh, S. 2006. Efficient Cross-validation of the complete Two stages in KFD Classifier Formulation, in Tang, Y.Y. et al(ed), Proceedings of the 18th International Conference on Pattern Recognition, Aug 20-24 2006, pp. 240-244. Hong Kong: IEEE.
    Source Title
    Proceedings of the 18th International Conference on Pattern Recognition Vol 3
    Source Conference
    18th International Conference on Pattern Recognition
    DOI
    10.1109/ICPR.2006.473
    ISBN
    0769525210
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/14950
    Collection
    • Curtin Research Publications
    Abstract

    This paper presents an efficient evaluation algorithm for cross-validating the two-stage approach of KFD classifiers. The proposed algorithm is of the same complexity level as the existing indirect efficient cross-validation methods but it is more reliable since it is direct and constitutes exact cross-validation for the KFD classifier formulation. Simulations demonstrate that the proposed algorithm is almost as fast as the existing fast indirect evaluation algorithm and the two-stage cross-validation selects better models on most of the thirteen benchmark data sets.

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