Competence-guided case-base editing techniques

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1898, Issue , 2000, Pages 186-197

  McKenna, Elizabeth ^a   Smyth, Barry ^a  

^a UNIVERSITY COLLEGE DUBLIN   (Ireland)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE; COMPUTERS;

CASE BASE; CASE BASED; CASE BASED CLASSIFIERS; CLASSIFICATION METHODS; CLASSIFICATION PERFORMANCE; CLASSIFICATION TIME; LAZY LEARNING; NEAREST NEIGHBOUR;

CASE BASED REASONING;

EID: 84948135390     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44527-7_17     Document Type: Conference Paper

References (19)

1. Aha, D. W., Kibler, D., and Albert, M. K.: Instance-Based Learning Algorithms, Machine Learning 6 (1991), 37-66.
2. Blake, C., Keogh, E., and Merz, C. J.: UCI repository of Machine Learning Databases, Irvine, CA: University of California. Department of Information and Computer Science, (1998)
3. Brighton, H.: Information Filtering for Lazy Learning Algorithms, Masters thesis, Centre for Cognitive Science, University of Edinburgh, Scotland, (1997).
4. Brighton, H and Mellish, C.: On the Consistency of information filters for Lazy learning algorithms, Proceedings of the 3rd European Conference on the Principles of Data Mining and Knowledge Discovery. Lecture Notes in Computer Science (Jan RauchJan M. Zytkow, ed.), Springer Verlag, (1999), pp. 283-288.
5. Cameron-Jones, R. M.: Minimum Description Length Case-Based Learning., Proceedings of the 5th Australian Joint Conference on Artificial Intelligence, World Scientific, (1992), pp. 368-373.
6. Chang, C. L.: Finding Prototypes for Nearest Neighbour Classifiers, IEEE Transactions on Computers C-23 (1974), 1179-1184.
7. Dasarathy, D V.: (ed.), Nearest Neighbor Norms: NN Pattern Classification Techniques, IEEE Press, (1991).
8. Gates, G. W.: The Reduced Nearest Neighbor Rule, IEEE Transactions on Information Theory IT-18(3) (1972), 431-433.
9. Hart, P. E.: The Condensed Nearest Neighbor Rule, IEEE Transactions on Information Theory IT-14 (1967), 515-516.
10. King, R. D., Feng, C. and Sutherland, A.: Statlog: Comparison of Classification Algorithms on Large Real-Worlds Problems, Applied Artificial Intelligence 9(3) (1995), 289-333.
11. McKenna, E. and Smyth, B.: Competence-guided Editing Methods for Lazy Learning, Proceedings of the 14th European Conference on Artificial Intelligence, (2000).
12. Smyth, B. and Keane, M. T.: Remembering to Forget: A Competence Preserving Case Deletion Policy for CBR Systems, Proceedings of the 14th International Joint Conference on Artificial Intelligence (Chris Mellish, ed.), Morgan Kaufmann, (1995), pp. 377-382.
13. Smyth, B. and McKenna, E.: Modelling the Competence of Case-Bases, Advances in Case-Based Reasoning. Lecture Notes in Artificial Intelligence (B. Smythan d P. Cunningham, eds.), Springer Verlag, (1998), pp. 208-220.
14. Smyth, B. and McKenna, E.: Building Compact Competent Case-Bases, Case-Based Reasoning Researchan d Development. Lecture Notes in Artificial Intelligence (Klaus Dieter Althoff, Ralph Bergmann, and L.Karl Branting, eds.), Springer Verlag, (1999), pp. 329-342.
15. Smyth, B. and McKenna, E.: Footprint-Based Retrieval, Case-Based Reasoning Researchan d Development. Lecture Notes in Artificial Intelligence (Klaus Dieter Althoff, Ralph Bergmann, and L.Karl Branting, eds.), Springer Verlag, (1999), pp. 343-357.
16. Smyth, B. and McKenna, E.: An Efficient and Effective Procedure for Updating a Competence Model for Case-Based Reasoners, Proceedings of the 11th European Conference on Machine Learning (Ramon Lopez de Mantaras and Enric Plaza, eds.), Springer Verlag, (2000).
17. Tomek, I.: Two Modifications of CNN, IEEE Transactions on Systems, Man, and Cybernetics 7(2) (1976), 679-772.
18. Wilson, D. L.: Asymptotic Properties of Nearest Neighbor Rules Using Edited Data, IEEE Transactions on Systems, Man, and Cybernetics 2-3 (1972), 408-421
19. Wilson, D. R. and Martinez, T. R.: Instance Pruning Techniques, Proceedings of the 14th International Conference on Machine Learning (D. Fisher, ed.), Morgan Kaufmann, (1997), pp. 403-411.