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- W2079604266 abstract "In Experiment 1, subjects were trained on three ill-defined categories represented by 4, 8, and 12 exemplars. Learning was followed by either a classification test on old, new, and random exemplars or a recognition test in which each learning exemplar was presented with two foils, both equidistant to the learning exemplar, but one more similar to the category prototype than the other. In Experiment 2, category size was manipulated between subjects, followed by the recognition test. Recognition data indicated that increasing the number of learning exemplars did not increase the total amount of exemplar information retained for each category. In addition, the more prototypical foil was incorrectly recognized more often than the less prototypical foil. Classification data replicated previous findings that increasing category size in learning enhances classification of new exemplars. The results were interpreted in terms of the relative amounts of categorical and idiosyncratic information that were retained from the original learning stimuli. It was proposed that categorical information can become a more dominant determinant of performance as category size increases." @default.
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- W2079604266 title "Recognition vs. classification of ill-defined category exemplars" @default.
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- W2079604266 doi "https://doi.org/10.3758/bf03196966" @default.
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