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Volumn 2006, Issue , 2006, Pages 567-573

Mining relational data through correlation-based multiple view validation

Author keywords

Classification; Multi relational Data Mining; Multi view Learning; Relational Database

Indexed keywords

CLASSIFICATION (OF INFORMATION); CORRELATION METHODS; EMBEDDED SYSTEMS; KNOWLEDGE ENGINEERING; RELATIONAL DATABASE SYSTEMS; SET THEORY;

EID: 33749560103     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1150402.1150469     Document Type: Conference Paper
Times cited : (10)

References (22)
  • 1
    • 9444271884 scopus 로고    scopus 로고
    • Guide to the financial data set
    • A. Siebes and P. Berka, editors
    • P. Berka. Guide to the financial data set. In A. Siebes and P. Berka, editors, PKDD2000 Discovery Challenge, 2000.
    • (2000) PKDD2000 Discovery Challenge
    • Berka, P.1
  • 3
    • 27144489164 scopus 로고    scopus 로고
    • A tutorial on support vector machines for pattern recognition
    • C. J. C. Burges. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery, 2(2):121-167, 1998.
    • (1998) Data Mining and Knowledge Discovery , vol.2 , Issue.2 , pp. 121-167
    • Burges, C.J.C.1
  • 5
    • 14844283227 scopus 로고    scopus 로고
    • PAC generalization bounds for co-training
    • S. Dasgupta, M. L. Littman, and D. A. McAllester. PAC generalization bounds for co-training. In NIPS, pages 375-382, 2001.
    • (2001) NIPS , pp. 375-382
    • Dasgupta, S.1    Littman, M.L.2    McAllester, D.A.3
  • 6
    • 0032111421 scopus 로고    scopus 로고
    • Category learning through multi-modality sensing
    • V. R. de Sa and D. H. Ballard. Category learning through multi-modality sensing. Neural Computation, 10(5):1097-1117, 1998.
    • (1998) Neural Computation , vol.10 , Issue.5 , pp. 1097-1117
    • De Sa, V.R.1    Ballard, D.H.2
  • 7
    • 0011177327 scopus 로고    scopus 로고
    • S. Dzeroski and N. Lavrac. editors, Springer, Berlin
    • S. Dzeroski and N. Lavrac. editors, Relational Data Mining. Springer, Berlin, 2001.
    • (2001) Relational Data Mining
  • 9
    • 84880688943 scopus 로고    scopus 로고
    • Learning probabilistic relational models
    • N. Friedman, L. Getoor, D. Koller, and A. Pfeffer. Learning probabilistic relational models. In IJCAI, pages 1300-1309, 1999.
    • (1999) IJCAI , pp. 1300-1309
    • Friedman, N.1    Getoor, L.2    Koller, D.3    Pfeffer, A.4
  • 13
    • 0027580356 scopus 로고
    • Very simple classification rules perform well on most commonly used datasets
    • R. C. Holte. Very simple classification rules perform well on most commonly used datasets. Mach. Learn., 11(1):63-90, 1993.
    • (1993) Mach. Learn. , vol.11 , Issue.1 , pp. 63-90
    • Holte, R.C.1
  • 14
    • 0031381525 scopus 로고    scopus 로고
    • Wrappers for feature subset selection
    • R. Kohavi and G. H. John. Wrappers for feature subset selection. Artificial Intelligence, 97(1-2):273-324, 1997.
    • (1997) Artificial Intelligence , vol.97 , Issue.1-2 , pp. 273-324
    • Kohavi, R.1    John, G.H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.