Fast and de-noise support vector machine training method based on fuzzy clustering method for large real world datasets

Turkish Journal of Electrical Engineering and Computer Sciences

Volumn 24, Issue 1, 2016, Pages 219-233

  Almasi, Omid Naghash ^a   Rouhani, Modjtaba ^a  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

Convex hull; Fuzzy clustering method; Noisy training dataset; QHull algorithm; Reduction set method; Support vector machine

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; COMPUTATIONAL GEOMETRY; FUZZY CLUSTERING; FUZZY SYSTEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; SUPPORT VECTOR MACHINES; TUNNELING (EXCAVATION);

CONVEX HULL; FUZZY CLUSTERING METHOD; GENERALIZATION ABILITY; GENERALIZATION PERFORMANCE; MACHINE LEARNING METHODS; REAL-WORLD DATASETS; TRAINING DATASET; TWO-STAGE METHODS;

CLASSIFICATION (OF INFORMATION);

EID: 84950295459     PISSN: 13000632     EISSN: 13036203     Source Type: Journal    
DOI: 10.3906/elk-1304-139     Document Type: Article

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