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Volumn , Issue , 2011, Pages 1239-1246
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Studying the behavior of a multiobjective genetic algorithm to design fuzzy rule-based classification systems for imbalanced data-sets
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Author keywords
feature selection; Fuzzy Rule Based Classification Systems; granularity level; imbalanced data sets; Multiobjective Genetic Algorithms
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Indexed keywords
CLASS DISTRIBUTIONS;
EXPERIMENTAL ANALYSIS;
FUZZY RULE BASED CLASSIFICATION SYSTEMS;
GRANULARITY LEVELS;
IMBALANCED DATA-SETS;
LOW COMPLEXITY;
MULTI-OBJECTIVE GENETIC ALGORITHM;
MULTIOBJECTIVE APPROACH;
OPEN PROBLEMS;
REAL APPLICATIONS;
SINGLE-OBJECTIVE GENETIC ALGORITHMS;
FEATURE EXTRACTION;
FUZZY RULES;
FUZZY SYSTEMS;
MULTIOBJECTIVE OPTIMIZATION;
GENETIC ALGORITHMS;
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EID: 80053085826
PISSN: 10987584
EISSN: None
Source Type: Conference Proceeding
DOI: 10.1109/FUZZY.2011.6007436 Document Type: Conference Paper |
Times cited : (6)
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References (8)
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