Combination of multiple diverse classifiers using belief functions for handling data with imperfect labels

Expert Systems with Applications

Volumn 39, Issue 2, 2012, Pages 1698-1707

  Tabassian, Mahdi ^a,b   Ghaderi, Reza ^a   Ebrahimpour, Reza ^b,c  

^a BABOL NOSHIRVANI UNIVERSITY OF TECHNOLOGY   (Iran)

^b INSTITUTE FOR RESEARCH IN FUNDAMENTAL SCIENCES IPM   (Iran)

^c SHAHID RAJAEE TEACHER TRAINING UNIVERSITY   (Iran)

Author keywords

Belief functions framework; Classifier selection; Data with imperfect labels; Ensemble learning; Neural network

Indexed keywords

BASIC BELIEF ASSIGNMENT; BELIEF FUNCTION; CLASS LABELS; CLASSIFICATION RESULTS; CLASSIFIER SELECTION; DATA WITH IMPERFECT LABELS; DEMPSTER-SHAFER THEORY OF EVIDENCE; ENSEMBLE CLASSIFIERS; ENSEMBLE LEARNING; LEARNING DATA; MULTI-LAYER PERCEPTRON NEURAL NETWORKS; TEST PATTERN; TRAINING DATA; TRAINING PATTERNS;

CLASSIFICATION (OF INFORMATION); FORMAL LOGIC; NEURAL NETWORKS; UNCERTAINTY ANALYSIS;

DATA HANDLING;

EID: 80054898828     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.06.061     Document Type: Conference Paper

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