Undersampling approach for imbalanced training sets and induction from multi-label text-categorization domains

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

Volumn 5669 LNAI, Issue , 2010, Pages 40-52

  Dendamrongvit, Sareewan ^a   Kubat, Miroslav ^a  

^a University of Miami College of Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPLICATION DOMAINS; BELONG TO; BINARY CLASSIFIERS; CLASSIFICATION PERFORMANCE; MULTI-LABEL; MULTI-LABEL CLASSIFICATIONS; TEXT CATEGORIZATION; TRAINING SETS; UNDER-SAMPLING;

CLASSIFICATION (OF INFORMATION); CLASSIFIERS; DATA MINING; INFORMATION RETRIEVAL SYSTEMS; TECHNICAL PRESENTATIONS;

TEXT PROCESSING;

EID: 77957042586     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-14640-4_4     Document Type: Conference Paper

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