Fast n-fold cross-validation for regularized least-squares

Publications of the Finnish Artificial Intelligence Society

Volumn , Issue , 2006, Pages 83-90

  Pahikkala, Tapio ^a   Boberg, Jorma ^a   Salakoski, Tapio ^a  

^a UNIVERSITY OF TURKU   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMEDICAL TEXT; C-V METHOD; COMPUTATIONAL ADVANTAGES; CROSS VALIDATION; DATA SETS; EIGEN DECOMPOSITION; FAST LEAVE-ONE-OUT; FORMAL PROOFS; KERNEL FUNCTION; KERNEL MATRICES; KERNEL-BASED LEARNING; LEARNING MACHINES; LEAST SQUARE; LEAST SQUARES SUPPORT VECTOR MACHINES; MACHINE LEARNING PROBLEM; POOR PERFORMANCE; REGULARIZATION PARAMETERS; RLS ALGORITHMS; SMALL SCALE; STATE-OF-THE-ART MACHINE LEARNING METHODS; TRAINING DATA;

ARTIFICIAL INTELLIGENCE; SUPPORT VECTOR MACHINES;

LEARNING ALGORITHMS;

EID: 84862520910     PISSN: 1796623X     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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