Learning from partially supervised data using mixture models and belief functions

Pattern Recognition

Volumn 42, Issue 3, 2009, Pages 334-348

  Come E ^a,c   Oukhellou, L ^a,b   Denoeux T ^c   Aknin, P ^a  

^a logistique et organisation des transports   (France)

^b UNIVERSITÉ PARIS EST CRÉTEIL   (France)

^c UNIVERSITÉ DE TECHNOLOGIE DE COMPIÈGNE   (France)

Author keywords

Classification; Clustering; Dempster Shafer theory; EM algorithm; Mixture models; Partially supervised learning; Semi supervised learning; Transferable belief model

Indexed keywords

CLASSIFICATION (OF INFORMATION); FORMAL LOGIC; IMAGE SEGMENTATION; MAXIMUM PRINCIPLE; MIXTURES; UNCERTAINTY ANALYSIS;

CLUSTERING; DEMPSTER-SHAFER THEORY; EM ALGORITHMS; MIXTURE MODEL; PARTIALLY SUPERVISED LEARNING; SEMI- SUPERVISED LEARNING; TRANSFERABLE BELIEF MODEL;

SUPERVISED LEARNING;

EID: 54549108812     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2008.07.014     Document Type: Article

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