Managing imbalanced data sets in multi-label problems: A case study with the SMOTE algorithm

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

Volumn 8258 LNCS, Issue PART 1, 2013, Pages 334-342

  Giraldo Forero, Andrés Felipe ^a   Jaramillo Garzón, Jorge Alberto ^a,b   Ruiz Muñoz, José Francisco ^a   Castellanos Domínguez, César Germán ^a  

^a UNIVERSIDAD NACIONAL DE COLOMBIA   (Colombia)

^b INSTITUTO TECNOLÓGICO METROPOLITANO   (Colombia)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION PERFORMANCE; IMBALANCED DATA SETS; MACHINE LEARNING COMMUNITIES; MULTI-LABEL LEARNING; MULTI-LABEL PROBLEMS; NUMBER OF SAMPLES; OVERSAMPLING TECHNIQUE; REAL-WORLD PROBLEM;

LEARNING SYSTEMS; PATTERN RECOGNITION;

LEARNING ALGORITHMS;

EID: 84893190862     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-41822-8_42     Document Type: Conference Paper

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