Classification versus inference learning contrasted with real-world categories

Erin L. Jones, Brian H. Ross

Research output: Contribution to journalArticlepeer-review


Categories are learned and used in a variety of ways, but the research focus has been on classification learning. Recent work contrasting classification with inference learning of categories found important later differences in category performance. However, theoretical accounts differ on whether this is due to an inherent difference between the tasks or to the implementation decisions. The inherent-difference explanation argues that inference learners focus on the internal structure of the categories-what each category is like-while classification learners focus on diagnostic information to predict category membership. In two experiments, using real-world categories and controlling for earlier methodological differences, inference learners learned more about what each category was like than did classification learners, as evidenced by higher performance on a novel classification test. These results suggest that there is an inherent difference between learning new categories by classifying an item versus inferring a feature.

Original languageEnglish (US)
Pages (from-to)764-777
Number of pages14
JournalMemory and Cognition
Issue number5
StatePublished - 2011
Externally publishedYes


  • Categorization
  • Category learning
  • Classification learning
  • Inference learning

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)


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