Probabilistic novelty detection with support vector machines

IEEE Transactions on Reliability

Volumn 63, Issue 2, 2014, Pages 455-467

  Clifton, Lei ^a   Clifton, David A ^a   Zhang, Yang ^b   Watkinson, Peter ^c   Tarassenko, Lionel ^a   Yin, Hujun ^d  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b UNIVERSITY OF SHEFFIELD   (United Kingdom)

^c UNIVERSITY OF OXFORD   (United Kingdom)

^d UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

calibration; condition monitoring; novelty detection; one class classification; Support vector machine

Indexed keywords

CALIBRATION; CONDITION MONITORING;

CALIBRATION TECHNIQUES; CONDITIONAL CLASS PROBABILITIES; MULTI-CLASS CLASSIFICATION; NOVELTY DETECTION; ONE-CLASS CLASSIFICATION; PHYSIOLOGICAL CONDITION; PROBABILISTIC APPROACHES; SUPPORT VECTOR MACHINE (SVMS);

SUPPORT VECTOR MACHINES;

EID: 84902107109     PISSN: 00189529     EISSN: None     Source Type: Journal    
DOI: 10.1109/TR.2014.2315911     Document Type: Article

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