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    BMCBI
    2006
    142views more  BMCBI 2006»
    Improving the Performance of SVM-RFE to Select Genes in Microarray Data
    13 years 7 months ago
    Improving the Performance of SVM-RFE to Select Genes in Microarray Data
    Download  www.biomedcentral.com
    Background: Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. ...
    Yuanyuan Ding, Dawn Wilkins
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    IJCNN
    2008
    IEEE
    92views Neural Networks» more  IJCNN 2008»
    Ranking and selecting clustering algorithms using a meta-learning approach
    14 years 1 months ago
    Ranking and selecting clustering algorithms using a meta-learning approach
    Download  www.cin.ufpe.br
    Abstract— We present a novel framework that applies a metalearning approach to clustering algorithms. Given a dataset, our meta-learning approach provides a ranking for the candi...
    Marcílio Carlos Pereira de Souto, Ricardo B...
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    ICMLA
    2010
    133views Machine Learning» more  ICMLA 2010»
    Smoothing Gene Expression Using Biological Networks
    13 years 5 months ago
    Smoothing Gene Expression Using Biological Networks
    Download  math.bu.edu
    Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
    Yue Fan, Mark A. Kon, Shinuk Kim, Charles DeLisi
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    KDD
    2004
    ACM
    139views Data Mining» more  KDD 2004»
    Learning a complex metabolomic dataset using random forests and support vector machines
    14 years 7 months ago
    Learning a complex metabolomic dataset using random forests and support vector machines
    Download  math.uc.edu
    Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
    Young Truong, Xiaodong Lin, Chris Beecher
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    FLAIRS
    2004
    239views Artificial Intelligence» more  FLAIRS 2004»
    Gene Expression Data Classification with Revised Kernel Partial Least Squares Algorithm
    13 years 8 months ago
    Gene Expression Data Classification with Revised Kernel Partial Least Squares Algorithm
    Download  www.aaai.org
    One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
    ZhenQiu Liu, Dechang Chen
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