Efficient two stage voting architecture for pairwise multi-label classification

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

Volumn 6464 LNAI, Issue , 2010, Pages 164-173

  Madjarov, Gjorgji ^a   Gjorgjevikj, Dejan ^a   Delev, Tomche ^a  

^a SS CYRIL AND METHODIUS UNIVERSITY   (Macedonia)

Author keywords

calibration; classification; Multi label; ranking

Indexed keywords

BINARY CLASSIFIERS; CLASSIFICATION; CONCURRENT ALGORITHMS; DECOMPOSITION STRATEGY; MAJORITY VOTING; MULTI-CLASS; MULTI-LABEL; MULTI-LABEL CLASSIFICATIONS; PREDICTION PERFORMANCE; QUADRATIC NUMBER; RANKING; RANKING METHODS; REAL-WORLD DATASETS; TRANSFORMATION METHODS; TWO STAGE; WEIGHTED VOTING;

ARTIFICIAL INTELLIGENCE; CALIBRATION; CLASSIFIERS; DATA PROCESSING;

ALGORITHMS;

EID: 78650798323     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-17432-2_17     Document Type: Conference Paper

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