Graph-based generation of a meta-learning search space
References
- Bensusan, H., Giraud-Carrier, C. and Kennedy, C.J. (2000). A higher-order approach to meta-learning,J. Cussens and A. Frisch (Eds.),, Springer-Verlag, Berlin/Heidelberg, pp. 33-42.
- Brazdil, P., Giraud-Carrier, C., Soares, C. and Vilalta, R. (2009)., Springer, Berlin/Heidelberg.
- Brazdil, P., Soares, C. and da Costa, J.P. (2003). Ranking learning algorithms: Using IBL and meta-learning on accuracy and time results,(3): 251-277.
- Chan, P. and Stolfo, S.J. (1996). On the accuracy of metalearning for scalable data mining,(1): 5-28.
- Czarnowski, I. and J˛edrzejowicz, P. (2011). Application of agent-based simulated annealing and tabu search procedures to solving the data reduction problem,(1): 57-68, DOI: 10.2478/v10006-011-0004-3.
- Duch, W. and Grudzi´nski, K. (1999). Search and global minimization in similarity-based methods,, p. 742.
- Duch,W. and Itert, L. (2003). Committees of undemocratic competent models,, pp. 33-36.
- Duch, W., Wieczorek, T., Biesiada, J. and Blachnik, M. (2004). Comparison of feature ranking methods based on information entropy,, pp. 1415-1420.
- Frank, A. and Asuncion, A. (2010). UCI machine learning repository, University of California, School of Information and Computer Science, Irvine, CA, http://archive.ics.uci.edu/ml.
- Gra˛bczewski, K. and Jankowski, N. (2011). Saving time and memory in computational intelligence system with machine unification and task spooling,(5): 570-588.
- Guyon, I. (2003). NIPS 2003 workshop on feature extraction, http://www.clopinet.com/isabelle/Projects/NIPS2003.
- Guyon, I. (2006). Performance prediction challenge, http://www.modelselect.inf.ethz.ch.
- Guyon, I., Gunn, S., Nikravesh, M. and Zadeh, L. (Eds.) (2006)., Springer, Berlin/Heidelberg.
- Jankowski, N., Duch, W. and Gra˛bczewski, K. (Eds.) (2011)., Studies in Computational Intelligence, Vol. 358, Springer, Berlin/Heidelberg.
- Jankowski, N. and Gra˛bczewski, K. (2005). Heterogenous committees with competence analysis,N. Nedjah, L. Mourelle, M. Vellasco, A. Abraham and M. Köppen (Eds.),, IEEE Press, New York, NY, pp. 417-422.
- Jankowski, N. and Gra˛bczewski, K. (2007). Handwritten digit recognition-Road to contest victory,IEEE Press, New York, NY, pp. 491-498.
- Jankowski, N. and Grochowski, M. (2004). Comparison of instances selection algorithms I: Algorithms survey,L. Rutkowski, I. Siekmann, R. Tadeusiewicz and L.A. Zadeh (Eds.),, Lecture Notes in Artifical Intelligence, Vol. 3070, Springer-Verlag, Berlin/Heidelberg pp. 598-603.
- Jankowski, N. and Grochowski, M. (2005). Instances selection algorithms in the conjunction with LVQ,M.H. Hamza (Ed.),, ACTA Press, Innsbruck, pp. 453-459.
- Kadlec, P. and Gabrys, B. (2008). Learnt topology gating artificial neural networks,, pp. 2605-2612.
- Kohonen, T. (1986). Learning vector quantization for pattern recognition,, Helsinki University of Technology, Espoo.
- Kordík, P. and ˇCerný, J. (2011). Self-organization of supervised models,N. Jankowski, W. Duch and K. Gra˛bczewski (Eds.),, Studies in Computational Intelligence, Vol. 358, Springer, Berlin/Heidelberg, pp. 179-223.
- Korytkowski, M., Nowicki, R., Rutkowski, L. and Scherer, R. (2011). AdaBoost ensemble of DCOG rough-neuro-fuzzy systems,P. J˛edrzejowicz, N.T. Nguyen and K. Hoang (Eds.),, Lecture Notes in Computer Science, Vol. 6922, Springer, Berlin/Heidelberg, pp. 62-71.
- Ł˛eski, J. (2003). A fuzzy if-then rule-based nonlinear classifier,(2): 215-223.
- Peng, Y., Falch, P., Soares, C. and Brazdil, P. (2002). Improved dataset characterisation for meta-learning,, pp. 141-152.
- Pfahringer, B., Bensusan, H. and Giraud-Carrier, C. (2000). Meta-learning by landmarking various learning algorithms,, pp. 743-750.
- Prodromidis, A. and Chan, P. (2000). Meta-learning in distributed data mining systems: Issues and approaches,H. Kargupta and P. Chan (Eds.),, AAAI Press, Menlo Park, CA.
- Scherer, R. (2010). Designing boosting ensemble of relational fuzzy systems,(5): 381-388.
- Scherer, R. (2011). An ensemble of logical-type neuro-fuzzy systems,(10): 13115-13120.
- Smith-Miles, K.A. (2008). Towards insightful algorithm selection for optimization using meta-learning concepts,, pp. 4117-4123.
- Todorovski, L. and Dzeroski, S. (2003). Combining classifiers with meta decision trees,(3): 223-249.
- Tro´c, M. and Unold, O. (2010). Self-adaptation of parameters in a learning classifier system ensemble machine,(1): 157-174, DOI: 10.2478/v10006-010-0012-8.
- Witten, I.H. and Frank, E. (2005)., Morgan Kaufmann, Amsterdam.
Language: English
Page range: 647 - 667
Published on: Sep 28, 2012
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Related subjects:
© 2012 Norbert Jankowski, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.