C4.5: programs for machine learning
C4.5: programs for machine learning
Case-based reasoning
The nature of statistical learning theory
The nature of statistical learning theory
Unifying instance-based and rule-based induction
Machine Learning
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Case-Based Reasoning: Experiences, Lessons and Future Directions
Case-Based Reasoning: Experiences, Lessons and Future Directions
Learning to Adapt for Case-Based Design
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Case Retrieval Nets: Basic Ideas and Extensions
KI '96 Proceedings of the 20th Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Acquiring case adaptation knowledge: a hybrid approach
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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When Case Based Reasoning systems are applied to real-world problems, the retrieved solutions in general require adaptations in order to be used on new contexts. Therefore, case adaptation is a desirable capability. However, case adaptation is still a challenge for this research area. In general, the the achievement of knowledge for case adaptation is harder than acquisition of cases. This paper proposes a hybrid approach for case adaptation able to learn adaptation knowledge from a Case Base.