Noncategorical approaches to feature prediction with uncertain categories

Papadopoulos, Christopher, Hayes, Brett K., and Newell, Ben R. (2011) Noncategorical approaches to feature prediction with uncertain categories. Memory and Cognition, 39. pp. 304-318.

[img] PDF (Published Version) - Published Version
Restricted to Repository staff only

View at Publisher Website:


In four experiments, we investigated how people make feature predictions about objects whose category membership is uncertain. Artificial visual categories were presented and remained in view while a novel instance with a known feature, but uncertain category membership was presented. All four experiments showed that feature predictions about the test instance were most often based on feature correlations (referred to as feature conjunction reasoning). Experiment 1 showed that feature conjunction reasoning was generally preferred to category-based induction in a feature prediction task. Experiment 2 showed that people used all available exemplars to make feature conjunction predictions. Experiments 3 and 4 showed that the preference for predictions based on feature conjunction persisted even when category-level information was made more salient and inferences involving a larger number of categories were required. Little evidence of reasoning based on the consideration of multiple categories (e.g., Anderson, (Psychological Review, 98:409–429, 1991)) or the single, most probable category (e.g., Murphy & Ross, (Cognitive Psychology, 27:148–193, 1994)) was found.

Item ID: 77259
Item Type: Article (Research - C1)
ISSN: 1532-5946
Copyright Information: © The Psychonomic Society 2010
Date Deposited: 24 Jan 2023 02:04
FoR Codes: 52 PSYCHOLOGY > 5204 Cognitive and computational psychology > 520401 Cognition @ 100%
SEO Codes: 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280121 Expanding knowledge in psychology @ 100%
Downloads: Total: 2
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page