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Volumn 2005, Issue , 2005, Pages 579-584

Data-driven decision tree learning algorithm based on rough set theory

Author keywords

Data driven; Decision tree; Pre pruning; Rough set

Indexed keywords

DATA REDUCTION; DECISION TABLES; DECISION THEORY; ROUGH SET THEORY;

EID: 33745683941     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (8)

References (16)
  • 1
    • 0004329558 scopus 로고    scopus 로고
    • Tsinghua university press, Beijing
    • Shi Z. Z, Knowledge discovery, Tsinghua university press, Beijing, 2002.
    • (2002) Knowledge Discovery
    • Shi, Z.Z.1
  • 2
    • 0042155226 scopus 로고    scopus 로고
    • Uncertainty measurement of decision table information systems
    • Wang G. Y., Uncertainty Measurement of Decision Table Information Systems, Computer science, 2001, 28 (5 special): 23-26.
    • (2001) Computer Science , vol.28 , Issue.5 SPECIAL , pp. 23-26
    • Wang, G.Y.1
  • 5
    • 0141791328 scopus 로고    scopus 로고
    • A self-learning model under uncertain condition
    • Wang G. Y., He X., A Self-learning Model under Uncertain Condition, Journal of Software, 2003, 14(6): 1096-1102.
    • (2003) Journal of Software , vol.14 , Issue.6 , pp. 1096-1102
    • Wang, G.Y.1    He, X.2
  • 7
  • 8
  • 9
    • 0002442571 scopus 로고
    • Discovering rules from large collections of examples: A case study
    • Michie D, ed. Edinburgh University Press
    • Quinlam J. R., Discovering rules from large collections of examples: a case study. Michie D, ed. Expert systems in the Micro electronic Age, Edinburgh University Press, 1979.
    • (1979) Expert Systems in the Micro Electronic Age
    • Quinlam, J.R.1
  • 10
    • 84866008319 scopus 로고    scopus 로고
    • Pre-pruning classification trees to reduce overfitting in noisy domains
    • (eds. H. Yin et al.), Springer-Verlag
    • M. Bramer. Pre-pruning Classification Trees to Reduce Overfitting in Noisy Domains. Intelligent Data Engineering and Automated Learning IDEAL 2002 (eds. H. Yin et al.), Springer-Verlag, 2002, 7-12.
    • (2002) Intelligent Data Engineering and Automated Learning IDEAL 2002 , pp. 7-12
    • Bramer, M.1
  • 11
    • 0003408496 scopus 로고    scopus 로고
    • UCI repository of machine learning databases
    • University of California, Department of Information and Computer Science, Irvine, CA
    • Blake C., Keogh E., Merz C. UCI repository of machine learning databases, Technical report, University of California, Department of Information and Computer Science, Irvine, CA.(1998) http://www.ics.uci.edy/~mlearn/MLRepository. html.
    • (1998) Technical Report
    • Blake, C.1    Keogh, E.2    Merz, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.