SMOTE-RSB*: A hybrid preprocessing approach based on oversampling and undersampling for high imbalanced data-sets using SMOTE and rough sets theory

Knowledge and Information Systems

Volumn 33, Issue 2, 2012, Pages 245-265

  Ramentol, Enislay ^a   Caballero, Yailé ^a   Bello, Rafael ^b   Herrera, Francisco ^c  

^a UNIVERSIDAD DE CAMAGÜEY   (Cuba)

^b CENTRAL UNIVERSITY OF LAS VILLAS   (Cuba)

^c UNIVERSITY OF GRANADA   (Spain)

Author keywords

Classification; Data preparation; Imbalanced data sets; Oversampling; Rough sets theory; Undersampling

Indexed keywords

APPROXIMATION ALGORITHMS; CLASSIFICATION (OF INFORMATION); LEARNING ALGORITHMS;

DATA PREPARATION; ELIMINATION OF SAMPLES; IMBALANCED DATA-SETS; LOWER APPROXIMATION; OVER SAMPLING; PREPROCESSING APPROACHES; SYNTHETIC MINORITY OVER-SAMPLING TECHNIQUES; UNDER-SAMPLING;

ROUGH SET THEORY;

EID: 84867715887     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-011-0465-6     Document Type: Article

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