Lambda pruning: An approximation of the string subsequence kernel for practical SVM classification and redundancy clustering

Advances in Data Analysis and Classification

Volumn 1, Issue 3, 2007, Pages 221-239

  Seewald, Alexander K ^a   Kleedorfer, Florian ^b  

^a Seewald Solutions   (Austria)

^b Research Studios Austria   (Austria)

Author keywords

Kernel methods; Machine learning; Memory consumption estimation; Runtime estimation; String kernels

Indexed keywords

CLUSTERING ALGORITHMS; COMPUTATIONAL COMPLEXITY; COMPUTER GRAPHICS; DATA REDUCTION; DATA STRUCTURES; LEARNING ALGORITHMS; STORAGE ALLOCATION (COMPUTER);

LAMBDA PRUNING; MEMORY CONSUMPTION ESTIMATION; RUNTIME ESTIMATION; STRING KERNELS; STRING SUBSEQUENCE KERNEL;

SUPPORT VECTOR MACHINES;

EID: 36549059067     PISSN: 18625347     EISSN: 18625355     Source Type: Journal    
DOI: 10.1007/s11634-007-0012-1     Document Type: Article

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