Learning from data with uncertain labels by boosting credal classifiers

Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data, U'09 in Conjunction with KDD'09

Volumn , Issue , 2009, Pages 38-47

  Quost, Benjamin ^a   Denoeux, Thierry ^a  

^a UNIVERSITÉ DE TECHNOLOGIE DE COMPIÈGNE   (France)

Author keywords

AdaBoost; Classification; Classifier combination; Dempster shafer theory; Theory of belief functions; Theory of evidence; Uncertainty

Indexed keywords

ADABOOST; ADABOOST ALGORITHM; BASIC BELIEF ASSIGNMENT; BELIEF FUNCTION; CLASSIFIER COMBINATION; DATA SETS; DEMPSTER-SHAFER THEORY; PARTIAL KNOWLEDGE; THEORY OF BELIEF FUNCTIONS; TRAINING DATA; TRAINING PATTERNS; UNCERTAIN LABELS;

CLASSIFIERS; DATA PROCESSING; FORMAL LOGIC; LABELS; LEARNING SYSTEMS; RELIABILITY; UNCERTAINTY ANALYSIS;

ADAPTIVE BOOSTING;

EID: 70450279156     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1610555.1610561     Document Type: Conference Paper

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