Nonlinear support vector machine visualization for risk factor analysis using nomograms and localized radial basis function kernels

IEEE Transactions on Information Technology in Biomedicine

Volumn 12, Issue 2, 2008, Pages 247-256

  Cho, Baek Hwan ^a   Yu, Hwanjo ^b,c   Lee, Jongshill ^a   Chee, Young Joon ^a   Kim, In Young ^a   Kim, Sun I ^a  

^a Hanyang University   (South Korea)

^b UNIVERSITY OF IOWA   (United States)

^c Pohang University of Science and Technology (POSTECH)   (South Korea)

Author keywords

Decision support systems; Feature selection; Localized radial basis function (LRBF) kernel; Nomograms; Support vector machines (SVMs); Visualization

Indexed keywords

BIOMEDICAL ENGINEERING; DECISION SUPPORT SYSTEMS; FEATURE EXTRACTION; RADIAL BASIS FUNCTION NETWORKS; RISK ASSESSMENT; VISUALIZATION;

LOCALIZED RADIAL BASIS FUNCTION (LRBF) KERNEL; RISK FACTOR ANALYSIS;

SUPPORT VECTOR MACHINES;

ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; COMPUTER INTERFACE; METHODOLOGY; NONLINEAR SYSTEM; PROGNOSIS; PROPORTIONAL HAZARDS MODEL; RISK ASSESSMENT; RISK FACTOR;

ARTIFICIAL INTELLIGENCE; COMPUTER GRAPHICS; DIAGNOSIS, COMPUTER-ASSISTED; NONLINEAR DYNAMICS; PATTERN RECOGNITION, AUTOMATED; PROGNOSIS; PROPORTIONAL HAZARDS MODELS; RISK ASSESSMENT; RISK FACTORS; USER-COMPUTER INTERFACE;

EID: 41549092817     PISSN: 10897771     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITB.2007.902300     Document Type: Article

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