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    ESANN
    2006
    157views Neural Networks» more  ESANN 2006»
    Data mining techniques for feature selection in blood cell recognition
    13 years 10 months ago
    Data mining techniques for feature selection in blood cell recognition
    Download  www.dice.ucl.ac.be
    The paper presents and compares the data mining techniques for selection of the diagnostic features in the problem of blood cell recognition in leukemia. Different techniques are c...
    Tomasz Markiewicz, Stanislaw Osowski
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    CORR
    2007
    Springer
    198views Education» more  CORR 2007»
    Clustering and Feature Selection using Sparse Principal Component Analysis
    13 years 9 months ago
    Clustering and Feature Selection using Sparse Principal Component Analysis
    Download  www.princeton.edu
    In this paper, we study the application of sparse principal component analysis (PCA) to clustering and feature selection problems. Sparse PCA seeks sparse factors, or linear combi...
    Ronny Luss, Alexandre d'Aspremont
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    ARTMED
    2007
    347views more  ARTMED 2007»
    A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature
    13 years 9 months ago
    A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature
    Download  ftp.esat.kuleuven.ac.be
    Objective: This study investigates the use of automated pattern recognition methods on magnetic resonance data with the ultimate goal to assist clinicians in the diagnosis of brai...
    Jan Luts, Arend Heerschap, Johan A. K. Suykens, Sa...
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    KDD
    2006
    ACM
    155views Data Mining» more  KDD 2006»
    Single-pass online learning: performance, voting schemes and online feature selection
    14 years 9 months ago
    Single-pass online learning: performance, voting schemes and online feature selection
    Download  www.cs.cmu.edu
    To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such a...
    Vitor R. Carvalho, William W. Cohen
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    CVPR
    2004
    IEEE
    211views Computer Vision» more  CVPR 2004»
    Face Localization via Hierarchical CONDENSATION with Fisher Boosting Feature Selection
    14 years 26 days ago
    Face Localization via Hierarchical CONDENSATION with Fisher Boosting Feature Selection
    Download  www.ifp.illinois.edu
    We formulate face localization as a Maximum A Posteriori Probability(MAP) problem of finding the best estimation of human face configuration in a given image. The a prior distribu...
    Jilin Tu, ZhenQiu Zhang, Zhihong Zeng, Thomas S. H...
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