Improving the performance of fuzzy rule based classification systems for highly imbalanced data-sets using an evolutionary adaptive inference system

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5517 LNCS, Issue PART 1, 2009, Pages 294-301

  Fernández, Alberto ^a   Del Jesus, María José ^b   Herrera, Francisco ^a  

^a UNIVERSITY OF GRANADA   (Spain)

^b UNIVERSITY OF JAÉN   (Spain)

Author keywords

Fuzzyrule based classification systems; Genetic fuzzy systems; Imbalanced data sets; Inference system; Parametric conjunction operators

Indexed keywords

FUZZYRULE-BASED CLASSIFICATION SYSTEMS; GENETIC FUZZY SYSTEMS; IMBALANCED DATA-SETS; INFERENCE SYSTEM; PARAMETRIC CONJUNCTION OPERATORS;

BACKPROPAGATION; FUZZY RULES; FUZZY SYSTEMS; NEURAL NETWORKS;

FUZZY INFERENCE;

EID: 68749115598     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02478-8_37     Document Type: Conference Paper

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