An enhanced Support Vector Machine classification framework by using Euclidean distance function for text document categorization

Applied Intelligence

Volumn 37, Issue 1, 2012, Pages 80-99

  Lee, Lam Hong ^a   Wan, Chin Heng ^a   Rajkumar, Rajprasad ^b   Isa, Dino ^b  

^a UNIVERSITI TUNKU ABDUL RAHMAN   (Malaysia)

^b UNIVERSITY OF NOTTINGHAM MALAYSIA CAMPUS   (Malaysia)

Author keywords

Euclidean distance function; Kernel function; Soft margin parameter; Support Vector Machine; Text document classification

Indexed keywords

AVERAGE DISTANCE; CLASSIFICATION ACCURACY; CLASSIFICATION DECISION; CRITICAL COMPONENT; CRITICAL PROBLEMS; DATA POINTS; DATA SETS; DECISION SURFACES; EUCLIDEAN DISTANCE; HIGH IMPACT; HIGH-DIMENSIONAL FEATURE SPACE; HYPER-PLANE; INPUT SPACE; KERNEL FUNCTION; MEASUREMENT TECHNIQUES; SOFT MARGINS; SUPPORT VECTOR; SUPPORT VECTOR MACHINE CLASSIFICATION; SVM CLASSIFICATION; SVM CLASSIFIERS; TEXT CLASSIFIERS; TEXT DOCUMENT; TRAINING DATA; TRAINING PHASE;

CLASSIFIERS; OPTIMIZATION; VECTOR SPACES;

SUPPORT VECTOR MACHINES;

EID: 84862586717     PISSN: 0924669X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10489-011-0314-z     Document Type: Article

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