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Volumn 1, Issue , 2005, Pages 537-542

Detection and prediction of distance-based outliers

Author keywords

Outlier detection; Outlier prediction

Indexed keywords

ALGORITHMS; MATHEMATICAL MODELS; PROBLEM SOLVING;

EID: 33644554469     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1066677.1066797     Document Type: Conference Paper
Times cited : (7)

References (16)
  • 8
    • 0029521676 scopus 로고
    • Sample compression; learnability, and the vapnik-chervonenkis dimension
    • S. Floyd and M. Warmuth. Sample compression; learnability, and the vapnik-chervonenkis dimension. Machine Learning, 211(3):269-304, 1995.
    • (1995) Machine Learning , vol.211 , Issue.3 , pp. 269-304
    • Floyd, S.1    Warmuth, M.2
  • 11
    • 0002948319 scopus 로고    scopus 로고
    • Algorithms for mining distance-based outliers in large datasets
    • E. Knorr and R. Ng. Algorithms for mining distance-based outliers in large datasets. In Proc. Int. Conf. on Very Large Databases, pages 392-403, 1998.
    • (1998) Proc. Int. Conf. on Very Large Databases , pp. 392-403
    • Knorr, E.1    Ng, R.2
  • 12
    • 0034133513 scopus 로고    scopus 로고
    • Distance-based outlier: Algorithms and applications
    • E. Knorr, R. Ng, and V. Tucakov. Distance-based outlier: algorithms and applications. VLDB Journal, 8(3-4):237-253, 2000.
    • (2000) VLDB Journal , vol.8 , Issue.3-4 , pp. 237-253
    • Knorr, E.1    Ng, R.2    Tucakov, V.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.