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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
    14 years 9 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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    BMCBI
    2007
    139views more  BMCBI 2007»
    Improving model predictions for RNA interference activities that use support vector machine regression by combining and filterin
    14 years 9 months ago
    Improving model predictions for RNA interference activities that use support vector machine regression by combining and filterin
    Download  www.biomedcentral.com
    Background: RNA interference (RNAi) is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathwa...
    Andrew S. Peek
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    BMCBI
    2005
    251views more  BMCBI 2005»
    Contextual weighting for Support Vector Machines in literature mining: an application to gene versus protein name disambiguation
    14 years 9 months ago
    Contextual weighting for Support Vector Machines in literature mining: an application to gene versus protein name disambiguation
    Download  www.biomedcentral.com
    Background: The ability to distinguish between genes and proteins is essential for understanding biological text. Support Vector Machines (SVMs) have been proven to be very effici...
    Tapio Pahikkala, Filip Ginter, Jorma Boberg, Jouni...
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    KDD
    2005
    ACM
    168views Data Mining» more  KDD 2005»
    Nomograms for visualizing support vector machines
    15 years 10 months ago
    Nomograms for visualizing support vector machines
    Download  stat.columbia.edu
    We propose a simple yet potentially very effective way of visualizing trained support vector machines. Nomograms are an established model visualization technique that can graphica...
    Aleks Jakulin, Martin Mozina, Janez Demsar, Ivan B...
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    ECCV
    2006
    Springer
    170views Computer Vision» more  ECCV 2006»
    Multivariate Relevance Vector Machines for Tracking
    15 years 11 months ago
    Multivariate Relevance Vector Machines for Tracking
    Download  mi.eng.cam.ac.uk
    This paper presents a learning based approach to tracking articulated human body motion from a single camera. In order to address the problem of pose ambiguity, a one-to-many mappi...
    Arasanathan Thayananthan, Ramanan Navaratnam, Bj&o...
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