A fast algorithm for training support vector regression via smoothed primal function minimization

International Journal of Machine Learning and Cybernetics

Volumn 6, Issue 1, 2015, Pages 155-166

  Zheng, Songfeng ^a  

^a MISSOURI STATE UNIVERSITY   (United States)

Author keywords

Conjugate gradient; Quadratic programming; Smooth approximation; Support vector regression; Insensitive loss function

Indexed keywords

COMPUTATIONAL EFFICIENCY; CONJUGATE GRADIENT METHOD; EFFICIENCY; QUADRATIC PROGRAMMING;

CONJUGATE GRADIENT ALGORITHMS; GRADIENT-BASED OPTIMIZATION METHOD; LOSS FUNCTIONS; QUADRATIC PROGRAMMING PROBLEMS; SEQUENTIAL MINIMIZATIONS; SMOOTH APPROXIMATION; SUPPORT VECTOR REGRESSION (SVR); UNCONSTRAINED MINIMIZATION PROBLEM;

SUPPORT VECTOR REGRESSION;

EID: 84921052011     PISSN: 18688071     EISSN: 1868808X     Source Type: Journal    
DOI: 10.1007/s13042-013-0200-6     Document Type: Article

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