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Prediction Performance as a Function of the Representation Language in Concept Formation Systems
Abstract
Existing concept formation systems employ diverse representation formalisms, ranging from logical to probabilistic, to describe acquired concepts. Those systems are usually evaluated in terms of their prediction performance and/or psychological validity. The evaluation studies, however, fail to take into account the underlying concept representation as one of the parameters that influence the system performance. So, whatever the outcome, the performance is bound to be interpreted as 'representation specific' This paper evaluates the performance of INC2, an incremental concept formation system, relative to the language used for representing concepts. The study includes the whole continuum, from logical to probabilistic representation. The results demonstrate the correctness of our assumption that performance does depend on the chosen concept representation language.
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