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Volumn 32, Issue 1, 2000, Pages 13-38

Constructing conjunctive attributes using production rules

Author keywords

Classification; Constructive Induction; Decision Tree Learning; Machine Learning

Indexed keywords


EID: 0038589195     PISSN: 1443458X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (2)

References (21)
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    • Department of Information and Computer Science, University of California, Irvine, CA
    • BLAKE, C., KEOGH, E., and MERZ, C.J. (1999): UCI Repository of Machine Learning Databases [http://www.ics.uci.edu/∼mlearn/MLRepository.html]. Department of Information and Computer Science, University of California, Irvine, CA.
    • (1999) UCI Repository of Machine Learning Databases
    • Blake, C.1    Keogh, E.2    Merz, C.J.3
  • 3
    • 0141771231 scopus 로고    scopus 로고
    • Data-driven constructive induction: Methodology and applications
    • Liu, H. and Motoda, H. (Eds.), Boston, MA: Kluwer Academic
    • BLOEDORN, E. and MICHALSKI, R.S. (1998b): Data-driven constructive induction: Methodology and applications. In Liu, H. and Motoda, H. (Eds.), Feature Extraction, Construction, and Selection: A Data Mining Perspective, Boston, MA: Kluwer Academic, 51-68.
    • (1998) Feature Extraction, Construction, and Selection: A Data Mining Perspective , pp. 51-68
    • Bloedorn, E.1    Michalski, R.S.2
  • 5
    • 0037575076 scopus 로고
    • Multivariate versus univariate decision trees
    • Department of Computer Science, University of Massachusetts, Amherst, MA
    • BRODLEY, C.E. and UTGOFF, P.E. (1992): Multivariate versus univariate decision trees. COINS Technical Report 92-8, Department of Computer Science, University of Massachusetts, Amherst, MA.
    • (1992) COINS Technical Report 92-8
    • Brodley, C.E.1    Utgoff, P.E.2
  • 8
    • 0008087071 scopus 로고
    • Technical Reports 927, Department of Computer Science, The University of Illinois at Urbana-Champaign, Urbana, IL
    • MICHALSKI, R.S. (1978): Pattern recognition as knowledge-guided computer induction. Technical Reports 927, Department of Computer Science, The University of Illinois at Urbana-Champaign, Urbana, IL.
    • (1978) Pattern Recognition As Knowledge-guided Computer Induction
    • Michalski, R.S.1
  • 9
    • 85140468046 scopus 로고
    • ID2-of-3: Constructive induction of M-of-N concepts for discriminators in decision trees
    • San Mateo, CA: Morgan Kaufmann
    • MURPHY, P.M. and Pazzani, M.J. (1991): ID2-of-3: Constructive induction of M-of-N concepts for discriminators in decision trees. Proceedings of the Eighth International Workshop on Machine Learning, San Mateo, CA: Morgan Kaufmann, 183-187.
    • (1991) Proceedings of the Eighth International Workshop on Machine Learning , pp. 183-187
    • Murphy, P.M.1    Pazzani, M.J.2
  • 11
    • 0025389210 scopus 로고
    • Boolean feature discovery in empirical learning
    • PAGALLO, G. and HAUSSLER, D. (1990): Boolean feature discovery in empirical learning. Machine Learning, 5:71-99.
    • (1990) Machine Learning , vol.5 , pp. 71-99
    • Pagallo, G.1    Haussler, D.2
  • 13
    • 0024627518 scopus 로고
    • Inferring decision trees using the minimum description length principle
    • QUINLAN, J.R. and RIVEST, R.L. (1989): Inferring decision trees using the minimum description length principle. Information and Computation, 80:227-248.
    • (1989) Information and Computation , vol.80 , pp. 227-248
    • Quinlan, J.R.1    Rivest, R.L.2
  • 16
    • 0001098776 scopus 로고
    • A universal prior for integers and estimation by minimum description length
    • RISSANEN, J. (1983): A universal prior for integers and estimation by minimum description length. Annals of Statistics, 11:416-431.
    • (1983) Annals of Statistics , vol.11 , pp. 416-431
    • Rissanen, J.1
  • 19
    • 0000599779 scopus 로고
    • Hypothesis-driven constructive induction in AQ17-HCI: A method and experiments
    • WNEK, J. and MICHALSKI, R.S. (1994): Hypothesis-driven constructive induction in AQ17-HCI: A method and experiments. Machine Learning, 14:139-168.
    • (1994) Machine Learning , vol.14 , pp. 139-168
    • Wnek, J.1    Michalski, R.S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.