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Volumn 54, Issue 3, 2004, Pages 187-193

Guest editorial: Introduction to the special issue on meta-learning

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; COST EFFECTIVENESS; DATA MINING; LEARNING ALGORITHMS;

EID: 1642379397     PISSN: 08856125     EISSN: None     Source Type: Journal    
DOI: 10.1023/B:MACH.0000015878.60765.42     Document Type: Editorial
Times cited : (135)

References (38)
  • 3
    • 0010644122 scopus 로고    scopus 로고
    • Theoretical models of learning to learn
    • (Chap. 4), Kluwer Academic Publishers, MA
    • Baxter, J. (1998). Theoretical models of learning to learn. Learning to Learn (Chap. 4, pp. 71-94), Kluwer Academic Publishers, MA.
    • (1998) Learning to Learn , pp. 71-94
    • Baxter, J.1
  • 4
    • 84881402977 scopus 로고    scopus 로고
    • God doesn't always shave with Occam's Razor - Learning when and how to prune
    • Springer
    • Bensusan, H. (1998). God doesn't always shave with Occam's Razor - Learning when and how to prune. In Proceedings of the Tenth European Conference on Machine Learning (pp. 119-124), Springer.
    • (1998) Proceedings of the Tenth European Conference on Machine Learning , pp. 119-124
    • Bensusan, H.1
  • 6
    • 0037361994 scopus 로고    scopus 로고
    • Ranking learning algorithms: Using IBL and meta-learning on accuracy and time results
    • Brazdil, P., Soares, C., & Pinto da Costa, J. (2003), Ranking learning algorithms: Using IBL and meta-learning on accuracy and time results. Machine Learning, 50:3, 251-277.
    • (2003) Machine Learning , vol.50 , Issue.3 , pp. 251-277
    • Brazdil, P.1    Soares, C.2    Pinto Da Costa, J.3
  • 8
    • 0002976263 scopus 로고
    • Recursive automatic bias selection for classifier construction
    • Brodley, C. E. (1995). Recursive automatic bias selection for classifier construction. Machine Learning, 20:1, 63-94.
    • (1995) Machine Learning , vol.20 , Issue.1 , pp. 63-94
    • Brodley, C.E.1
  • 11
    • 12444258560 scopus 로고
    • Evaluation and selection of biases in machine learning
    • DesJarding, M., & Gordon, D. F. (1995). Evaluation and selection of biases in machine learning. Machine Learning, 20:1, 5-22.
    • (1995) Machine Learning , vol.20 , Issue.1 , pp. 5-22
    • DesJarding, M.1    Gordon, D.F.2
  • 12
    • 12144288329 scopus 로고    scopus 로고
    • Is combining classifiers better than selecting the best one?
    • Dzeroski, S. & Zenko, B. (2004). Is combining classifiers better than selecting the best one? Machine Learning, 54:3, 195-209.
    • (2004) Machine Learning , vol.54 , Issue.3 , pp. 195-209
    • Dzeroski, S.1    Zenko, B.2
  • 15
    • 0003774150 scopus 로고
    • Active bias adjustment for incremental, supervised concept learning
    • PhD Thesis, University of Maryland
    • Gordon, D. F. (1990). Active bias adjustment for incremental, supervised concept learning. PhD Thesis, University of Maryland, 1990.
    • (1990)
    • Gordon, D.F.1
  • 17
    • 1642280141 scopus 로고    scopus 로고
    • On data and algorithms: Understanding learning performance
    • Kalousis, A., Gama, J., & Hilario, M. (2004). On data and algorithms: Understanding learning performance. Machine Learning, 54:3, 195-209.
    • (2004) Machine Learning , vol.54 , Issue.3 , pp. 195-209
    • Kalousis, A.1    Gama, J.2    Hilario, M.3
  • 19
    • 0010687619 scopus 로고
    • Dynamical selection of learning algorithms
    • D. Fisher & Fisher & H. J. Lenz (Eds.), Springer-Verlag
    • Merz, C. J. (1995). Dynamical selection of learning algorithms. In Learning from Data: Artificial Intelligence and Statistics, D. Fisher & Fisher & H. J. Lenz (Eds.), Springer-Verlag.
    • (1995) Learning from Data: Artificial Intelligence and Statistics
    • Merz, C.J.1
  • 21
    • 0012476755 scopus 로고    scopus 로고
    • Arbitrating among competing classifiers using learned referees
    • Ortega, J., Koppel, M., & Argamon, S. (2001). Arbitrating among competing classifiers using learned referees. Knowledge and Information Systems, 3, 470-490.
    • (2001) Knowledge and Information Systems , vol.3 , pp. 470-490
    • Ortega, J.1    Koppel, M.2    Argamon, S.3
  • 24
    • 0010643651 scopus 로고    scopus 로고
    • Second special issue on inductive transfer
    • Pratt, L., & Thrun, S. (1997). Second Special Issue on Inductive Transfer. Machine Learning, 28(1).
    • (1997) Machine Learning , vol.28 , Issue.1
    • Pratt, L.1    Thrun, S.2
  • 27
    • 1642328943 scopus 로고    scopus 로고
    • Optimal ordered problem solver
    • Schmidhuber, J. (2004). Optimal ordered problem solver. Machine Learning, 54:3, 195-209.
    • (2004) Machine Learning , pp. 195-209
    • Schmidhuber, J.1
  • 28
    • 1642276856 scopus 로고    scopus 로고
    • A meta-learning approach to select the kernel width in support vector regression
    • Soares, C., Brazdil, P., & Kuba, P. (2004). A meta-learning approach to select the kernel width in support vector regression, Machine Learning, 54:3, 195-209.
    • (2004) Machine Learning , vol.54 , Issue.3 , pp. 195-209
    • Soares, C.1    Brazdil, P.2    Kuba, P.3
  • 30
    • 0037365188 scopus 로고    scopus 로고
    • Combining classifiers with meta decision trees
    • Todorovski, L., & Dzeroski, S. (2003). Combining classifiers with meta decision trees Machine Learning, 50:3, 223-250.
    • (2003) Machine Learning , vol.50 , Issue.3 , pp. 223-250
    • Todorovski, L.1    Dzeroski, S.2
  • 32
    • 0010687621 scopus 로고    scopus 로고
    • Lifelong learning algorithms
    • (Chap. 8); MA: Kluwer Academic Publishers
    • Thrun, S. (1998). Lifelong learning algorithms. Learning to Learn (Chap. 8, pp. 181-209), MA: Kluwer Academic Publishers.
    • (1998) Learning to Learn , pp. 181-209
    • Thrun, S.1
  • 33
    • 0001164493 scopus 로고
    • Shift of bias for inductive concept learning
    • In R. S. Michalski, et al. (Ed.); California: Morgan Kaufman
    • Utgoff, P. (1986). Shift of bias for inductive concept learning. In R. S. Michalski, et al. (Ed.), Machine Learning: An Artificial Intelligence Approach, Vol. II, (pp. 107-148), California: Morgan Kaufman.
    • (1986) Machine Learning: An Artificial Intelligence Approach , vol.2 , pp. 107-148
    • Utgoff, P.1
  • 34
    • 0036782663 scopus 로고    scopus 로고
    • Many-layered learning
    • MIT Press
    • Utgoff, P., & Stracuzzi, D. J. (2003). Many-layered learning. Neural Networks, 14, 2497-2529, MIT Press.
    • (2003) Neural Networks , vol.14 , pp. 2497-2529
    • Utgoff, P.1    Stracuzzi, D.J.2
  • 36
    • 0030126609 scopus 로고    scopus 로고
    • Learning in the presence of concept drift and hidden contexts
    • Widmer, G., & Kubat, M. (1996). Learning in the presence of concept drift and hidden contexts. Machine Learning, 23:1, 69-101.
    • (1996) Machine Learning , vol.23 , Issue.1 , pp. 69-101
    • Widmer, G.1    Kubat, M.2
  • 37
    • 0031164523 scopus 로고    scopus 로고
    • Tracking context changes through meta-learning
    • Widmer, G. (1997). Tracking context changes through meta-learning. Machine Learning, 27:3, 259-286.
    • (1997) Machine Learning , vol.27 , Issue.3 , pp. 259-286
    • Widmer, G.1
  • 38
    • 0026692226 scopus 로고
    • Stacked generalization
    • Wolpert, D. (1992). Stacked Generalization. Neural Networks, 5, 241-259.
    • (1992) Neural Networks , vol.5 , pp. 241-259
    • Wolpert, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.