The odd one out: Identifying and characterising anomalies

Proceedings of the 11th SIAM International Conference on Data Mining, SDM 2011

Volumn , Issue , 2011, Pages 804-815

  Smets, Koen ^a   Vreeken, Jilles ^a  

^a UNIVERSITY OF ANTWERP   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

DIAGNOSIS;

CLASSIFICATION ACCURACY; MINIMUM DESCRIPTION LENGTH PRINCIPLE; NEGATIVE EXAMPLES; OBSERVATION ERRORS; OPTIMAL BOUNDARY; POSITIVE EXAMPLES; STATE-OF-THE-ART PERFORMANCE; TRANSACTION DATA;

DATA MINING;

EID: 84880091878     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972818.69     Document Type: Conference Paper

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