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Volumn 1983, Issue , 2000, Pages 48-53

Information-based classification by aggregating emerging patterns

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; ENGINEERING EDUCATION; INTELLIGENT AGENTS;

EID: 84944059303     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Conference Paper
Times cited : (33)

References (12)
  • 1
    • 0001882616 scopus 로고
    • Fast algorithm for mining association rules
    • R Agrawal and R Srikant. Fast algorithm for mining association rules. In Proc. VLDB’94, pages 487-499, 1994.
    • (1994) Proc. VLDB’94 , pp. 487-499
    • Agrawal, R.1    Srikant, R.2
  • 2
    • 0002034653 scopus 로고    scopus 로고
    • Efficient Mining of emerging patterns: Discovering trends and differences
    • G Dong and J Li. Efficient Mining of emerging patterns: Discovering trends and differences. In Proc. of KDD’99, 1999.
    • (1999) Proc. Of KDD’99
    • Dong, G.1    Li, J.2
  • 4
    • 0002593344 scopus 로고
    • Multi-interval discretization of continuous-valued attributes for classification learning
    • U M Fayyad and K B Irani. Multi-interval discretization of continuous-valued attributes for classification learning. In Proc. of IJCAI’93, 1993.
    • (1993) Proc. Of IJCAI’93
    • Fayyad, U.M.1    Irani, K.B.2
  • 5
    • 84944135340 scopus 로고    scopus 로고
    • Make use of the most expressive jumping emerging patterns for classification
    • Japan
    • J Li, G Dong, and K Ramamohanarao. Make use of the most expressive jumping emerging patterns for classification. In Proc. of PAKDD’00, Japan, 2000.
    • (2000) Proc. Of PAKDD’00
    • Li, J.1    Dong, G.2    Ramamohanarao, K.3
  • 6
    • 0002776254 scopus 로고    scopus 로고
    • Integrating classification and association rule mining
    • New York, USA, August
    • B Liu, W Hsu, and Y Ma. Integrating classification and association rule mining. In Proc. of KDD’98, New York, USA, pages 27-31, August 1998.
    • (1998) Proc. Of KDD’98 , pp. 27-31
    • Liu, B.1    Hsu, W.2    Ma, Y.3
  • 7
    • 0002356150 scopus 로고    scopus 로고
    • SLIQ: A fast scalable classifier for data mining
    • Avignon, France, March
    • M Mehta, R Agrawal, and J Rissanen. SLIQ: A fast scalable classifier for data mining. In Proc. of EDBT’96, Avignon, France, March 1996.
    • (1996) Proc. Of EDBT’96
    • Mehta, M.1    Agrawal, R.2    Rissanen, J.3
  • 8
    • 0013392343 scopus 로고    scopus 로고
    • Extending naive bayes classifiers using long itemsets
    • San Diego, USA, August
    • D Meretakis and B Wüthrich. Extending naive bayes classifiers using long itemsets. In Proc. of KDD’99, San Diego, USA, August 1999.
    • (1999) Proc. Of KDD’99
    • Meretakis, D.1    Wüthrich, B.2
  • 9
    • 0001098776 scopus 로고
    • A universal prior for integers and estimation by minimum description length
    • J Rissanen. A universal prior for integers and estimation by minimum description length. Annals of Statistics, 11:416-431, 1983.
    • (1983) Annals of Statistics , vol.11 , pp. 416-431
    • Rissanen, J.1
  • 10
    • 0000107517 scopus 로고
    • An information measure for classification
    • C Wallace and D Boulton. An information measure for classification. Computer Journal, 11:185-195, 1968.
    • (1968) Computer Journal , vol.11 , pp. 185-195
    • Wallace, C.1    Boulton, D.2
  • 12
    • 0034593078 scopus 로고    scopus 로고
    • Exploring constraints to efficiently mine emerging patterns from large high-dimensional datasets
    • Boston, USA, August
    • X Zhang, G Dong, and K Ramamohanarao. Exploring constraints to efficiently mine emerging patterns from large high-dimensional datasets. In Proc. of KDD’00, Boston, USA, August 2000.
    • (2000) Proc. Of KDD’00
    • Zhang, X.1    Dong, G.2    Ramamohanarao, K.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.