Performance evaluation of SVM and iterative FSVM classifiers with bootstrapping-based over-sampling and under-sampling

IEEE International Conference on Fuzzy Systems

Volumn 2015-November, Issue , 2015, Pages

  Zughrat, A ^a   Mahfouf, M ^a   Thornton, S ^b  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

^b SWINDEN TECHNOLOGY CENTRE   (Netherlands)

Author keywords

fuzzy support vector machines; imbalanced data; over sampling; support vectro machines; under sampling

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL COMPLEXITY; FUZZY SYSTEMS; ITERATIVE METHODS; LEARNING SYSTEMS; VECTORS;

CLASS IMBALANCE PROBLEMS; FUZZY SUPPORT VECTOR MACHINES; GENERALIZATION CAPABILITY; GENERALIZATION PERFORMANCE; IMBALANCED DATA; MACHINE LEARNING TECHNIQUES; OVER SAMPLING; UNDER-SAMPLING;

SUPPORT VECTOR MACHINES;

EID: 84975748741     PISSN: 10987584     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZ-IEEE.2015.7337850     Document Type: Conference Paper

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