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Bott, Lewis; Hoffman, Aaron B.; Murphy, Gregory L. – Journal of Experimental Psychology: General, 2007
Many theories of category learning assume that learning is driven by a need to minimize classification error. When there is no classification error, therefore, learning of individual features should be negligible. The authors tested this hypothesis by conducting three category-learning experiments adapted from an associative learning blocking…
Descriptors: Associative Learning, Classification, Error Patterns, Hypothesis Testing