Abstract
We propose a new case base maintenance strategy which allows the improvement of the prediction quality of CBR system. This strategy combines the learning of new selected cases, the reduction of the use of noise cases, and the removal of not useful cases. We describe in this paper the case based reasoning system, in which we have associated new measurements for the source cases. These measurements vary with the use of the cases to get target cases solutions.
This research is supported by Numsight Consulting.
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Zehraoui, F., Kanawati, R., Salotti, S. (2003). Case Base Maintenance for Improving Prediction Quality. In: Ashley, K.D., Bridge, D.G. (eds) Case-Based Reasoning Research and Development. ICCBR 2003. Lecture Notes in Computer Science(), vol 2689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45006-8_53
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DOI: https://doi.org/10.1007/3-540-45006-8_53
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