메뉴 건너뛰기




Volumn 218, Issue , 2010, Pages 84-98

Resource-bounded outlier detection using clustering methods

Author keywords

data cleaning; hierarchical clustering; Outlier detection; outlier ranking

Indexed keywords

CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; STATISTICS;

EID: 78049253616     PISSN: 09226389     EISSN: 18798314     Source Type: Book Series    
DOI: 10.3233/978-1-60750-633-1-84     Document Type: Article
Times cited : (3)

References (22)
  • 4
    • 0242666971 scopus 로고    scopus 로고
    • Data preparation for data mining
    • May
    • Shichao Zhang, Chengqi Zhang, and Qiang Yang and. Data preparation for data mining. Applied Artificial Intelligence, 17 (5 & 6):375-381, May 2003.
    • (2003) Applied Artificial Intelligence , vol.17 , Issue.5-6 , pp. 375-381
    • Zhang, S.1    Zhang, C.2    Yang, Q.3
  • 8
    • 0013058484 scopus 로고    scopus 로고
    • C5.0: An informal tutorial
    • R. Quinlan. C5.0: An Informal Tutorial. RuleQuest, 1998. http://www.rulequest.com/see5-unix.html.
    • (1998) RuleQuest
    • Quinlan, R.1
  • 9
    • 0003136237 scopus 로고
    • Efficient and efective clustering method for spatial data mining
    • R. Ng and J. Han. Efficient and efective clustering method for spatial data mining. In Proc. of VLDB'94, 1994.
    • (1994) Proc. of VLDB'94
    • Ng, R.1    Han, J.2
  • 11
    • 0000034040 scopus 로고
    • Complexities of hierarchic clustering algorithms: State of the art
    • F. Murtagh. Complexities of hierarchic clustering algorithms: state of the art. Computational Statistics Quarterly, 1:101-113, 1984.
    • (1984) Computational Statistics Quarterly , vol.1 , pp. 101-113
    • Murtagh, F.1
  • 12
    • 84863304598 scopus 로고    scopus 로고
    • R Development Core Team, R Foundation for Statistical Computing, ISBN 3-900051-07-0
    • R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, 2008. ISBN 3-900051-07-0.
    • (2008) R: A Language and Environment for Statistical Computing
  • 13
    • 0003910106 scopus 로고
    • Multidimensional clustering algorithms
    • Wuerzburg: Physica-Verlag
    • F. Murtagh. Multidimensional clustering algorithms. COMPSTAT Lectures 4, Wuerzburg: Physica-Verlag, 1985.
    • (1985) COMPSTAT Lectures , vol.4
    • Murtagh, F.1
  • 16
    • 7544223741 scopus 로고    scopus 로고
    • A survey of outlier detection methodologies
    • Victoria Hodge; Jim Austin. A survey of outlier detection methodologies. Artificial Intelligence Review, 22:85-126, 2004.
    • (2004) Artificial Intelligence Review , vol.22 , pp. 85-126
    • Hodge, V.1    Austin, J.2
  • 17
    • 0004235843 scopus 로고
    • Chapman and Hall, 11 New Fetter Lane, London EC4P 4EE
    • D. M. Hawkins. Identification of Outliers. Chapman and Hall, 11 New Fetter Lane, London EC4P 4EE, 1980.
    • (1980) Identification of Outliers
    • Hawkins, D.M.1
  • 21
    • 9444228878 scopus 로고    scopus 로고
    • Predicting outliers
    • N. Lavrac, D. Gamberger, L. Todorovski, and H. Blockeel, editors, number LNAI in 2838, Springer
    • L. Torgo and R. Ribeiro. Predicting outliers. In N. Lavrac, D. Gamberger, L. Todorovski, and H. Blockeel, editors, Proceedings of Principles of Data Mining and Knowledge Discovery (PKDD'03), number LNAI in 2838, pages 447-458. Springer, 2003.
    • (2003) Proceedings of Principles of Data Mining and Knowledge Discovery (PKDD'03) , pp. 447-458
    • Torgo, L.1    Ribeiro, R.2
  • 22
    • 0003790115 scopus 로고    scopus 로고
    • The effect of class distribution on classifier learning: An empirical study
    • Department of computer science, Rutgers University
    • G. Weiss and F. Provost. The effect of class distribution on classifier learning: an empirical study. Technical Report ML-TR-44, Department of computer science, Rutgers University, 2001.
    • (2001) Technical Report ML-TR-44
    • Weiss, G.1    Provost, F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.