Measures of Solution Accuracy in Case-Based Reasoning Systems
Conference paper
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.
Keywords
Membership Function High Confidence Confusion Matrix Solution Accuracy Confidence Calculation
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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