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    CATA
    2009
    186views Computer Science» more  CATA 2009»
    Nearest Shrunken Centroid as Feature Selection of Microarray Data
    13 years 6 months ago
    Nearest Shrunken Centroid as Feature Selection of Microarray Data
    Download  public.clunet.edu
    The nearest shrunken centroid classifier uses shrunken centroids as prototypes for each class and test samples are classified to belong to the class whose shrunken centroid is nea...
    Myungsook Klassen, Nyunsu Kim
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    ICNC
    2005
    Springer
    163views Applied Computing» more  ICNC 2005»
    Support Vector Based Prototype Selection Method for Nearest Neighbor Rules
    13 years 10 months ago
    Support Vector Based Prototype Selection Method for Nearest Neighbor Rules
    Download  sci2s.ugr.es
    The Support vector machines derive the class decision hyper planes from a few, selected prototypes, the support vectors (SVs) according to the principle of structure risk minimizat...
    Yuangui Li, Zhonghui Hu, Yunze Cai, Weidong Zhang
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    ICPR
    2002
    IEEE
    125views computer vision» more  ICPR 2002»
    Prototype Selection for Finding Efficient Representations of Dissimilarity Data
    14 years 6 months ago
    Prototype Selection for Finding Efficient Representations of Dissimilarity Data
    Download  ict.ewi.tudelft.nl
    The nearest neighbor (NN) rule is a simple and intuitive method for solving classification problems. Originally, it uses distances to the complete training set. It performs well, ...
    Elzbieta Pekalska, Robert P. W. Duin
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    HIS
    2004
    194views Information Technology» more  HIS 2004»
    Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
    13 years 6 months ago
    Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
    Download  eprints.iisc.ernet.in
    Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
    T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
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    PAA
    2006
    89views Distributed And Parallel Com...» more  PAA 2006»
    Efficient median based clustering and classification techniques for protein sequences
    13 years 5 months ago
    Efficient median based clustering and classification techniques for protein sequences
    Download  eprints.iisc.ernet.in
    Abstract In this paper, an efficient K-medians clustering (unsupervised) algorithm for prototype selection and Supervised K-medians (SKM) classification technique for protein seque...
    P. A. Vijaya, M. Narasimha Murty, D. K. Subramania...
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