Complexity Profiling for Informed Case-Base Editing
The contents of the case knowledge container is critical to the performance of case-based classification systems. However the knowledge engineer is given little support in the selection of suitable techniques to maintain and monitor the case-base. In this paper we present a novel technique that provides an insight into the structure of a case-base by means of a complexity profile that can assist maintenance decision-making and provide a benchmark to assess future changes to the case-base. We also introduce a complexity-guided redundancy reduction algorithm which uses a local complexity measure to actively retain cases close to boundaries. The algorithm offers control over the balance between maintaining competence and reducing case-base size. The ability of the algorithm to maintain accuracy in a compacted case-base is demonstrated on seven public domain classification datasets.
KeywordsDecision Boundary Reduction Algorithm Relative Cover Knowledge Engineer Zero Complexity
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- 1.Aha, D., Kibler, D., Albert, M.: Instance-based learning algorithms. Machine Learning 6(1), 37–66 (1991)Google Scholar
- 2.Blake, C., Keogh, E., Merz, C.: UCI repository of machine learning databases (1998)Google Scholar
- 3.Brighton, H., Mellish, C.: Identifying competence-critical instances for instance-based learners. In: Instance Selection and Construction for Data Mining, pp. 77–94 (2001)Google Scholar
- 7.Francis, A., Ram, A.: Computational models of the utility problem and their application to a utility analysis of case-based reasoning. In: Proceedings of the Workshop on Knowledge Compilation and Speed-Up Learning (1993)Google Scholar
- 9.Massie, S., Craw, S., Wiratunga, N.: Complexity-guided case discovery for case based reasoning. In: Proceedings of the 20th National Conference on Artificial Intelligence, pp. 216–221 (2005)Google Scholar
- 10.McKenna, E., Smyth, B.: A competence model for case-based reasoning. In: 9th Irish Conference on Artificial Intelligence and Cognitive Science (1998)Google Scholar
- 11.McKenna, E., Smyth, B.: Competence-guided case-base editing techniques. In: Proceedings of the 5th European Workshop on Case-Based Reasoning, pp. 186–197 (2000)Google Scholar
- 13.Richter, M.: Introduction. In: Case-Based Reasoning Technology: From Foundations to Applications, pp. 1–15 (1998)Google Scholar
- 14.Smyth, B., Cunningham, P.: The utility problem analysed: A case-based reasoning perspective. In: Proceedings of the 3rd European Workshop on Case-Based Reasoning, pp. 392–399 (1996)Google Scholar
- 15.Smyth, B., Keane, M.T.: Remembering to forget. In: Proceedings of the 14th International Joint Conference on Artificial Intelligence, pp. 377–382 (1995)Google Scholar