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Online learning


[1] T.M. Kwok, D.Y. Yeung, Objective Functions for Training New Hidden Units In Constructive Neural Networks. IEEE Trans. On Neural Networks, vol. 8(5), 1999, pp.1131-1148
[2] Wei-Min Shen, Efficient Incremental Induction of Decision Lists - Can Incremental Learning Outperform Non-Incremental Learning?, Technical Report, USC-ISI-96-012, Information Sciences Institute, University of Southern California, 1996.
[3] W. Duch, J. Mandziuk, Challenges for Computational Intelligence. Studies in Computational Intelligence Series, Springer 2007
[4] G.D. Weber, Beam Search in Incremental Rule Learning, Proc. of the Fourteenth Midwest Artificial Intelligence and Cognitive Science Conference, Cincinnati, Ohio, 2003
[5] C. Giraud-Carrier, A Note on the Utility of Incremental Learning, AI Communications, 13(4), pp. 215–223, 2000
[6] I. Guyon, S. Gunn, M. Nikravesh, L. Zadeh, Feature Extraction, Foundations and Applications, Series Studies in Fuzziness and Soft Computing, Physica-Verlag, Springer, 2006.
[7] J. A. Lee, M. Verleysen, Nonlinear Dimensionality Reduction, Series Information Science and Statistics, Springer, 2007
[8] J. Lim, D. Ross, R. Lin, M. Yang, Incremental Learning for Visual Tracing, Proceedings NIPS’2004, 2004
[9] T. Wieczorek, M. Blachnik, K. Mączka, Building a model for time reduction of steel scrap meltdown in the electric arc furnace (EAF). General strategy with a comparison of feature selection methods. Zgłoszone na: International Conference on Artificial Intelligence and Soft Computing, Zakopane, 2008
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[11] F. d’Alche-Buc, L. Ralaivola, Incremental Learning Algorithms for Classification and Regression: local strategies,
[12] N. Cristianini, J. Shawe-Taylor, An Introduction to Support Vector Machine and other kernel-based methids, Cambridge University Press, 2000
[13] S. Ruping, Incremental Learning wih Support Vector Machines, Proceedings of the 2001 IEEE International Conference on Data Mining (ICDM '01), pp. 641-642, IEEE, 2001.
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[15] P.E. Utgoff, Incremental Induction of Decision Trees, Proc. of the Eleventh International Conference on Machine Learning , Morgan-Kaufmann, pp. 318-325, 1994
[16] R. Schmidt, B. Pollwein, L. Gierl, Experiences with Case-Based Reasoning Methods and Prototypes for Medical Knowledge-Based Systems., Lecture Notes in Computer Science, vol. 1620, Springer Verlag, Denmark, 1999
[17] Stanfill C., Waltz D., Toward memory-based reasoning., Communications of the ACM, vol.~29(12), pp 1213-1228, 1986
[18] Aha D., Kibler D., Albert M.K., Instance-Based Learning Algorithms, Machine Learning, vol.~6, Kluwer Academic Publishers, pp. 37-66, 1991
[19] Wess S., Altho K.D., Derwand G., Using k-d trees to improve the retrieval step in case-based reasoning, Topics in Case-Based Reasoning, Springer Verlag, pp 167–181., Berlin, 1994
[20] Plaza E., Aamodt A., Case-based Reasoning-Fundamental Issues, Methodological Variations, and System Approaches., AICOM, vol.~7(1), pp. 39-59, 1994
[21] Clark P., Niblett T., The CN2 Induction Algorithm, Machine Learning Jurnal, vol.~3(4), pp.261-283, 1989

notatki/ci/douczanie.txt · Last modified: 2019/03/21 13:06 (external edit)