Active learning methods for electrocardiographic signal classification

IEEE Transactions on Information Technology in Biomedicine

Volumn 14, Issue 6, 2010, Pages 1405-1416

  Pasolli, Edoardo ^a   Melgani, Farid ^a  

^a UNIVERSITY OF TRENTO   (Italy)

Author keywords

Active learning; electrocardiographic (ECG) signal classification; support vector machine (SVM)

Indexed keywords

ACTIVE LEARNING; ACTIVE LEARNING METHODS; CLASSIFICATION PROCESS; ECG SIGNALS; EXPERIMENTAL STUDIES; LEARNING STRATEGY; POSTERIOR PROBABILITY; QUERY BY COMMITTEES; SIGNAL CLASSIFICATION; SIMULATED DATA; SUPPORT VECTOR MACHINE (SVM); SUPPORT VECTOR MACHINE CLASSIFICATION; TRAINING SETS; UNLABELED DATA;

ELECTROCHROMIC DEVICES; SUPPORT VECTOR MACHINES;

ELECTROCARDIOGRAPHY;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; CLASSIFICATION; COMPUTER SIMULATION; ELECTROCARDIOGRAPHY; FACTUAL DATABASE; HUMAN; METHODOLOGY; PRINCIPAL COMPONENT ANALYSIS; SIGNAL PROCESSING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DATABASES, FACTUAL; ELECTROCARDIOGRAPHY; HUMANS; PRINCIPAL COMPONENT ANALYSIS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 78249264429     PISSN: 10897771     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITB.2010.2048922     Document Type: Article

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