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    HIS
    2004
    91views Information Technology» more  HIS 2004»
    Hybrid Learning Scheme for Data Mining Applications
    14 years 11 months ago
    Hybrid Learning Scheme for Data Mining Applications
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    Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directl...
    T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
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    BMCBI
    2008
    107views more  BMCBI 2008»
    A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
    14 years 10 months ago
    A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
    Download  www.biomedcentral.com
    Background: A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essential for the development of more reliable algorithms for high-throughp...
    Cong Zhou, Lucas D. Bowler, Jianfeng Feng
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    BIOINFORMATICS
    2006
    105views more  BIOINFORMATICS 2006»
    Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure
    14 years 10 months ago
    Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure
    Download  noble.gs.washington.edu
    Darrin P. Lewis, Tony Jebara, William Stafford Nob...
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    BIOINFORMATICS
    2005
    79views more  BIOINFORMATICS 2005»
    VizRank: finding informative data projections in functional genomics by machine learning
    14 years 9 months ago
    VizRank: finding informative data projections in functional genomics by machine learning
    Download  www.ailab.si
    Gregor Leban, Ivan Bratko, Uros Petrovic, Tomaz Cu...
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    BIOINFORMATICS
    2002
    61views more  BIOINFORMATICS 2002»
    Machine learning of functional class from phenotype data
    14 years 9 months ago
    Machine learning of functional class from phenotype data
    Download  users.aber.ac.uk
    Amanda Clare, Ross D. King
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