Efficient leave-m-out cross-validation of support vector regression by generalizing decremental algorithm

New Generation Computing

Volumn 27, Issue 4, 2009, Pages 307-318

  Karasuyama, Masayuki ^a   Takeuchi, Ichiro ^a   Nakano, Ryohei ^b  

^a NAGOYA INSTITUTE OF TECHNOLOGY   (Japan)

^b CHUBU UNIVERSITY   (Japan)

Author keywords

Decremental Algorithm; Path following; Support Vector Regression

Indexed keywords

BREAK-POINTS; COMPUTATIONAL COSTS; COMPUTATIONALLY EFFICIENT; CROSS VALIDATION; DATA POINTS; DECREMENTAL ALGORITHMS; LEAVE-ONE-OUT; PATH FOLLOWING; SUPPORT VECTOR REGRESSIONS; SVM MODEL; TRAINING SETS;

ALGORITHMS; COST REDUCTION; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES; VECTORS;

COMPUTATIONAL EFFICIENCY;

EID: 70450206749     PISSN: 02883635     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00354-008-0067-3     Document Type: Article

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