Approximate l-fold cross-validation with least squares SVM and kernel ridge regression

Proceedings - 2013 12th International Conference on Machine Learning and Applications, ICMLA 2013

Volumn 1, Issue , 2013, Pages 58-64

  Edwards, Richard E ^a   Zhang, Hao ^a   Parker, Lynne E ^a   New, Joshua R ^b  

^a University of Tennessee Knoxville   (United States)

^b OAK RIDGE NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; REGRESSION ANALYSIS;

APPROXIMATE METHODS; CROSS-VALIDATION METHODS; KERNEL APPROXIMATION; KERNEL RIDGE REGRESSIONS; LEAST SQUARES SUPPORT VECTOR MACHINES; LEAST SQUARES SVM; MEMORY REQUIREMENTS; SCALABILITY ISSUE;

SUPPORT VECTOR MACHINES;

EID: 84899410000     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLA.2013.18     Document Type: Conference Paper

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