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A Feature-Salience Analogue of the Inverse Base-rate Effect
Corey J. Bohil,Arthur B. Markman,W. odd Maddox 대한사고개발학회 2005 The International Journal of Creativity & Problem Vol.15 No.1
Classification learning requires integrating many properties of the items being learned including the base-rate probability that a category will occur as well as the salience of features. Previous research has demonstrated an inverse base-rate effect, in which people classify an item that has features predictive of both a high base-rate and low base-rate category into the rarer category. We suggest that this finding reflects that feature salience plays a greater role in classification than does base-rates. We tested this hypothesis by demonstrating that manipulations of feature salience determine the classification of ambiguous stimuli regardless of the underlying base-rates of the categories.