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To improve the precision of memory-based reasoning (MBR) for ordinal data, this article presents correlation-based similarity metrics. The basic idea of this research is an intuitive assumption: if the correlation between the answer and one feature in a sample data set is large, the weight of this feature for predication should be large. To validate this proposal, we promote “leave-one-out cross-validation”...
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