An approach to data reduction and integrated machine classification

New Generation Computing

Volumn 28, Issue 1, 2010, Pages 21-40

  Czarnowski, Ireneusz ^a   Jȩdrzejowicz, Piotr ^a  

^a GDYNIA MARITIME UNIVERSITY   (Poland)

Author keywords

Agent based Algorithm; Classification; Data Mining; Data Reduction; Integrated Machine Classification; Machine Learning

Indexed keywords

AGENT BASED; AGENT-BASED ALGORITHM; CLASSIFICATION; INTEGRATED MACHINES; MACHINE-LEARNING;

CLASSIFICATION (OF INFORMATION); DATA MINING; INTEGRATION; LEARNING ALGORITHMS; LEARNING SYSTEMS; POPULATION STATISTICS;

DATA REDUCTION;

EID: 77149122401     PISSN: 02883635     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00354-008-0073-5     Document Type: Conference Paper

References (38)

1. D.W. Aha D. Kibler M.K. Albert 1991 "Instance-based learning algorithms" Machine Learning 6 37 66
2. Aksela, M., Adaptive Combinations of Classifiers with Application to On-line Handwritten Character Recognition, Ph.D. Thesis, Department of Computer Science and Engineering, Helsinki University of Technology, Helsinki, 2007.
3. Asuncion, A., Newman, D.J., "UCI Machine Learning Repository," Irvine, CA: University of California, School of Information and Computer Science, http://www.ics.uci.edu/~mlearn/MLRepository.html, 2007.
4. Barbucha, D., Czarnowski, I., J drzejowicz, P., Ratajczak-Ropel, E. and Wierzbowska, I., "JADE-Based A-Team as a Tool for Implementing Population- Based Algorithms," in Proc. of the Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06) (Yuehui Chen, Ajith Abraham eds.) IEEE Computer Society, 3, pp. 144-149, 2006.
5. B. Bhanu J. Peng 2000 "Adaptive Integration Image Segmentation and Object Recognition" IEEE Trans. on Systems, Man and Cybernetics 30 4 427 441 10.1109/5326.897070 (Pubitemid 32190900)
6. Bull, L., "Learning Classifier Systems: A Brief Introduction," in Applications of Learning Classifier Systems, Studies in Fuzziness and Soft Computing (Larry Bull ed.), Springer, 2004.
7. Cano, J. R., Herrera, F., Lozano, M., "On the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining," in Pattern Recognition Letters, Elsevier, 2004.
8. C.-L. Chang 1974 "Finding Prototypes for Nearest Neighbor Classifier" IEEE Transactions on Computers 23 11 1179 1184 0292.68044 10.1109/T-C.1974.223827
9. Czarnowski, I., J drzejowicz, P., "An Approach to Instance Reduction in Supervised Learning," in Research and Development in Intelligent Systems XX (Coenen F., Preece A. and Macintosh A. eds.), Springer, London, pp. 267-282, 2004.
10. Dash, M., Liu, H., "Feature Selection for Classification," Intelligence Data Analysis, 1, 3, pp. 131-156, 1997.
11. Duch, W., "Results - Comparison of Classification," Nicolaus Copernicus University, http://www.is.umk.pl/projects/datasets.html, 2002.
12. Frawley, W. J., Piatetsky-Shapiro, G. and Matheus, C., "Knowledge Discovery in Databases - An Overview," in Knowledge Discovery in Databases (Piatetsky- Shapiro G., Matheus C. eds.) AAAI/MIT Press, 1991.
13. Glover, F., "Tabu search. Part I and II," ORSA Journal of Computing, 1, 3, Summer 1990 and 2, 1, Winter 1990.
14. Han, J., Kamber, M., Data Mining. Concepts and Techniques, Academic Press, San Diego, 2001.
15. E. Hart P. 1968 "The Condensed Nearest Neighbor Rule" IEEE Transactions on Information Theory 14 515 516 10.1109/TIT.1968.1054155
16. Ishibuchi, H., Nakashima, T. and Nii, M., "Learning of Neural Networks with GA-based Instance Selection," in Proc. of the IFSA World Congress and 20th NAFIPS International Conference, 4, pp. 2102-2107, 2001.
17. Holland, J. H., "Adaptation," in Progress in Theoretical Biology (Rosen & Snell eds.), 4, Plenum, 1976.
18. P. Jȩdrzejowicz 1999 "Social Learning Algorithm as a Tool for Solving Some Difficult Scheduling Problems" Foundation of Computing and Decision Sciences 24 51 66
19. R. Kohavi H. John G. 1997 "Wrappers for Feature Subset Selection" Artificial Intelligence 97 1-2 273 324 0904.68143 10.1016/S0004-3702(97)00043-X
20. Lazarevic, A., Obradovic, Z., "Data Reduction Using Multiple Models Integration," in Proc. of the 5th European Conference Principles and Practice of Knowledge Discovery and Databases, LNCS 2168, Springer-Verlag London, pp. 301-313, 2001.
21. Liu, H., Lu, H., Yao, J., "Identifying relevant databases for multidatabase mining," in Proc. of the Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 210-221, 1998.
22. Meiri, R., Zahavi, J., "Using Simulated Annealing to Optimize the Feature Selection Problem in Marketing Applications," European Journal of Operational Research, 17, 3, pp. 842-858, 2006.
23. Michalewicz, Z., Genetic Algorithms + Data Structures = Evolution Programs, Springer, Berlin, 1996.
24. J. Morgan R. Daugherty A. Hilchie B. Carey 2003 "Sample size and modeling accuracy of decision tree based data mining tools" Academy of Information and Management Science Journal 6 2 71 99
25. Quinlan, J. R., C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers, San Mateo, 1993.
26. Raman, B., Ioerger, T. R., "Enhancing learning using feature and example selection," in Journal of Machine Learning Research, 2003.
27. G. L. Ritter H. B. Woodruff S. R. Lowry T. L. Isenhour 1975 "An Algorithm for a Selective Nearest Decision Rule" IEEE Trans. on Information Theory 21 665 669 0323.68023 10.1109/TIT.1975.1055464
28. A. Rozsypal M. Kubat 2003 "Selecting Representative Examples and Attributes by a Genetic Algorithm" Intelligent Data Analysis 7 4 291 304 1083.68590
29. Sahel, Z., Bouchachia, A., Gabrys, B., Rogers P., "Adaptive Mechanisms for Classification Problems with Drifting Data." in KES 2007 (B. Apolloni et al. eds.), LNAI 4693, Springer-Verlag, pp. 419-426, 2007.
30. Skalak, D. B., "Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithm," in Proc. of the International Conference on Machine Learning, pp. 293-301, 1994.
31. Talukdar, S., Baerentzen, L., Gove, A. and De Souza, P., "Asynchronous Teams: Cooperation Schemes for Autonomous. Computer-Based Agents," Technical Report EDRC 18-59-96, Carnegie Mellon University, Pittsburgh, 1996.
32. I. Tomek 1976 "An Experiment with the Edited Nearest-Neighbor Rule" IEEE Trans. on Systems, Man, and Cybernetics 6 6 448 452 0332.68081 10.1109/TSMC.1976.4309523 428853
33. D. R. Wilson T. R. Martinez 2000 "An integrated instance-based learning algorithm" Computational Intelligence 16 1 28 10.1111/0824-7935. 00103 1744715
34. Wilson, D. R., Martinez, T. R., "Reduction Techniques for Instance-based Learning Algorithm," Machine Learning, 33, 3, Kluwer Academic Publishers, Boston, pp. 257-286, 2000.
35. Witten, I. H., Frank, E., Data Mining: Practical Machine Learning Tools and Techniques with JAVA Implementations, Morgan Kaufmann, San Francisco, 2003.
36. Wroblewski, J., Adaptacyjne metody klasyfikacji obiektow, Ph.D. Thesis, University of Warsaw, Warsaw (in Polish), 2001.
37. EL-Manzalawy, Y., Honavar, V., "WLSVM: Integrating LibSVM into Weka Environment," Software available at http://www.cs.iastate.edu/~yasser/ wlsvm, 2005.
38. Zongker, D., Jain, A., "Algorithm for Feature Selection: An Evaluation," in Proc. of the International Conference on Pattern Recognition, ICPR '96, pp. 18-22, 1996.