Inlier-based outlier detection via direct density ratio estimation

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2008, Pages 223-232

  Hido, Shohei ^a   Tsuboi, Yuta ^a   Kashima, Hisashi ^a   Sugiyama, Masashi ^b   Kanamori, Takafumi ^c  

^a IBM RESEARCH   (United States)

^b TOKYO INSTITUTE OF TECHNOLOGY   (Japan)

^c NAGOYA UNIVERSITY   (Japan)

Author keywords

Density ratio; Importance; Outlier detection

Indexed keywords

CLOSED FORM SOLUTIONS; CLOSED-FORM FORMULAE; CROSS VALIDATION; DENSITY ESTIMATION; DENSITY RATIO; HIGH-DIMENSIONAL PROBLEMS; IMPORTANCE; LEAVE-ONE-OUT ERROR; MASSIVE DATA SETS; OUTLIER DETECTION; REAL-WORLD DATASETS; REGULARIZATION PARAMETERS; SEMIPARAMETRIC; STATISTICAL APPROACH; TEST DATA; TEST SETS; TRAINING SETS; TUNING PARAMETER;

ESTIMATION; INFORMATION MANAGEMENT; MINING;

PARAMETER ESTIMATION;

EID: 67049098640     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2008.49     Document Type: Conference Paper

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