Titlebook: Case-Based Reasoning Research and Development; 26th International C Michael T. Cox,Peter Funk,Shahina Begum Conference proceedings 2018 Spr

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H. Baumgärtl,W. Zimelka,D. W. Lübbers cases” and exploits them to broaden the range of cases available for competence-based deletion. Experimental results support that this method increases competence and quality retention for less representative case bases. They also reveal the unexpected result that ECC can improve retention of compe

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A History of Infant Intelligence Testing,in classification and prediction tasks in particular. We propose a larger understanding, beyond instance-based learning, of case based learning as analogical learning that would promote it as a major contributor of the analogizer approach of machine learning.

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Optical Switching in Low-Dimensional Systemsvestigation. Here we evaluate an algorithm called Tangent Recognition Anomaly Pruning to eliminate false starts that arise in interactive dialogues created within our case-based reasoning system called Ronin. Results show that Tangent Recognition Anomaly Pruning is an effective algorithm for processing mistakes when reusin case reuse.

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CEC-Model: A New Competence Model for CBR Systems Based on the Belief Function Theorysituations. Therefore, this paper presents a new competence model called . which manages uncertainty during both of cases clustering and similarity measurement using a powerful tool called the belief function theory.

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