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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 9 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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    VLDB
    2007
    ACM
    164views Database» more  VLDB 2007»
    A new intrusion detection system using support vector machines and hierarchical clustering
    14 years 9 months ago
    A new intrusion detection system using support vector machines and hierarchical clustering
    Download  www.utdallas.edu
    Whenever an intrusion occurs, the security and value of a computer system is compromised. Network-based attacks make it difficult for legitimate users to access various network ser...
    Latifur Khan, Mamoun Awad, Bhavani M. Thuraisingha...
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    ICDM
    2009
    IEEE
    160views Data Mining» more  ICDM 2009»
    Fast Online Training of Ramp Loss Support Vector Machines
    14 years 3 months ago
    Fast Online Training of Ramp Loss Support Vector Machines
    Download  www.ist.temple.edu
    —A fast online algorithm OnlineSVMR for training Ramp-Loss Support Vector Machines (SVMR s) is proposed. It finds the optimal SVMR for t+1 training examples using SVMR built on t...
    Zhuang Wang, Slobodan Vucetic
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    ICARCV
    2002
    IEEE
    109views Robotics» more  ICARCV 2002»
    Quantized wavelet features and support vector machines for on-road vehicle detection
    14 years 1 months ago
    Quantized wavelet features and support vector machines for on-road vehicle detection
    Download  www.cse.unr.edu
    The focus of this work is on the problem of feature selection and classification for on-road vehicle detection. In particular, we propose using quantized Haar wavelet features an...
    Zehang Sun, George Bebis, Ronald Miller
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    BMCBI
    2010
    151views more  BMCBI 2010»
    Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
    13 years 8 months ago
    Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
    Download  www.biomedcentral.com
    Background: Because a priori knowledge about function of G protein-coupled receptors (GPCRs) can provide useful information to pharmaceutical research, the determination of their ...
    Zhanchao Li, Xuan Zhou, Zong Dai, Xiaoyong Zou
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