A general Lp-norm support vector machine via mixed 0-1 programming

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7376 LNAI, Issue , 2012, Pages 40-49

  Nguyen, Hai Thanh ^a   Franke, Katrin ^a  

^a NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

Author keywords

branch and bound; feature selection; mixed 0 1 quadratic programming; support vector machine

Indexed keywords

0-1 LINEAR PROGRAMMING; 0-1 PROGRAMMING; BRANCH AND BOUNDS; BRANCH-AND-BOUND ALGORITHMS; CLASSIFICATION ACCURACY; DATA SETS; FEATURE SELECTION PROBLEM; FEATURE SUBSET; GENERALIZATION CAPABILITY; L1 NORM; L2-NORM; LINEAR CONSTRAINTS; LP-NORM; NONLINEAR PROGRAMMING PROBLEM; OPTIMIZATION PROBLEMS; REDUNDANT FEATURES; SUPPORT VECTOR;

ALGORITHMS; CLASSIFICATION (OF INFORMATION); DATA MINING; FEATURE EXTRACTION; LINEAR PROGRAMMING; OPTIMIZATION; PATTERN RECOGNITION; PROBLEM SOLVING; QUADRATIC PROGRAMMING;

SUPPORT VECTOR MACHINES;

EID: 84864910469     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-31537-4_4     Document Type: Conference Paper

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