Abstract
The case-based reasoning (CBR) methodology can be augmented with the ability to determine the confidence in the correctness of individual solutions. A confidence calculation can be added to the REUSE portion of the CBR methodology. The confidence calculation takes confidence indicators, like “number of cases retrieved with best solution” and “average similarity of cases which suggest an alternative solution,” and generates a confidence value. The information gain algorithm C4.5 can be used to select the best confidence indicators by evaluating their usefulness in historical cases. A genetic algorithm can be used to optimize and maintain the confidence calculation.
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Cheetham, W., Price, J. (2004). Measures of Solution Accuracy in Case-Based Reasoning Systems. In: Funk, P., González Calero, P.A. (eds) Advances in Case-Based Reasoning. ECCBR 2004. Lecture Notes in Computer Science(), vol 3155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28631-8_9
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DOI: https://doi.org/10.1007/978-3-540-28631-8_9
Publisher Name: Springer, Berlin, Heidelberg
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