메뉴 건너뛰기




Volumn 1, Issue , 2006, Pages 500-505

A fast decision tree learning algorithm

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTATIONAL COMPLEXITY; DATA STRUCTURES; DECISION TABLES; LEARNING SYSTEMS; TREES (MATHEMATICS);

EID: 33750742739     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (146)

References (16)
  • 2
    • 0031361611 scopus 로고    scopus 로고
    • Machine learning research: Four current directions
    • Dietterich, T. G. 1997. Machine learning research: Four current directions. AI Magazine 18:4:97-136.
    • (1997) AI Magazine , vol.18 , Issue.4 , pp. 97-136
    • Dietterich, T.G.1
  • 3
    • 0031269184 scopus 로고    scopus 로고
    • Beyond independence: Conditions for the optimality of the simple Bayesian classifier
    • Domingos, P., and Pazzani, M. 1997. Beyond independence: Conditions for the optimality of the simple Bayesian classifier. Machine Learning 29:103-130.
    • (1997) Machine Learning , vol.29 , pp. 103-130
    • Domingos, P.1    Pazzani, M.2
  • 5
    • 33750711226 scopus 로고    scopus 로고
    • Learning from little: Comparison of classifiers given little training
    • Forman, G., and Cohen, I. 2004. Learning from little: Comparison of classifiers given little training. In Proceeding of PKDD2004. 161-172.
    • (2004) Proceeding of PKDD2004 , pp. 161-172
    • Forman, G.1    Cohen, I.2
  • 7
    • 23044519492 scopus 로고    scopus 로고
    • Rainforest - A framework for fast decision tree construction of large datasets
    • Gehrke, J. E.; Ramakrishnan, R.; and Ganti, V. 2000. Rainforest - A framework for fast decision tree construction of large datasets. Data Mining and Knowledge Discovery 4:2/3:127-162.
    • (2000) Data Mining and Knowledge Discovery , vol.4 , Issue.2-3 , pp. 127-162
    • Gehrke, J.E.1    Ramakrishnan, R.2    Ganti, V.3
  • 8
    • 0027580356 scopus 로고
    • Very simple classification rules perform well on most commonly used datasets
    • Holte, R. 1993. Very simple classification rules perform well on most commonly used datasets. Machine Learning 11:63-91.
    • (1993) Machine Learning , vol.11 , pp. 63-91
    • Holte, R.1
  • 11
    • 1242268938 scopus 로고    scopus 로고
    • Tree induction vs. logistic regression: A learning-curve analysis
    • Perlich, C.; Provost, F.; and Simonoff, J. S. 2003. Tree induction vs. logistic regression: A learning-curve analysis. Machine Learning Research 4:211-255.
    • (2003) Machine Learning Research , vol.4 , pp. 211-255
    • Perlich, C.1    Provost, F.2    Simonoff, J.S.3
  • 12
    • 0141771188 scopus 로고    scopus 로고
    • A survey of methods for scaling up inductive algorithms
    • Provost, F. J., and Kolluri, V. 1999. A survey of methods for scaling up inductive algorithms. Data Min. Knowl. Discov 3(2):131-169.
    • (1999) Data Min. Knowl. Discov , vol.3 , Issue.2 , pp. 131-169
    • Provost, F.J.1    Kolluri, V.2
  • 15
    • 0026119038 scopus 로고
    • Symbolic and neural network learning algorithms: An experimental comparison
    • Shavlik, J.; Mooney, R.; and Towell, G. 1991. Symbolic and neural network learning algorithms: An experimental comparison. Machine Learning 6:111-143.
    • (1991) Machine Learning , vol.6 , pp. 111-143
    • Shavlik, J.1    Mooney, R.2    Towell, G.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.