Feature selection and granularity learning in genetic fuzzy rule-based classification systems for highly imbalanced data-sets

International Journal of Uncertainty, Fuzziness and Knowldege-Based Systems

Volumn 20, Issue 3, 2012, Pages 369-397

  Villar, Pedro ^a   FernÁndez, Alberto ^b   Carrasco, Ramón A ^a   Herrera, Francisco ^a  

^a UNIVERSITY OF GRANADA   (Spain)

^b UNIVERSITY OF JAÉN   (Spain)

Author keywords

Feature selection; Fuzzy rule based classification systems; Genetic algorithms; Granularity level; Imbalanced data sets

Indexed keywords

CLASSIFICATION (OF INFORMATION); FEATURE SELECTION; FUZZY INFERENCE; FUZZY RULES; LEARNING ALGORITHMS;

APPLICATION AREA; CLASS DISTRIBUTIONS; COMPACT MODEL; FEATURES SELECTION; FUZZY RULE BASED CLASSIFICATION SYSTEMS; GENETIC-FUZZY; GRANULARITY LEVELS; IMBALANCED DATASET; INTERPRETABILITY; REAL APPLICATIONS;

GENETIC ALGORITHMS;

EID: 84862112830     PISSN: 02184885     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218488512500195     Document Type: Article

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