Jarecki,J.B.
Meder,B.
Nelson,J.D.

This paper investigates the role of the assumption of class- conditional independence of object features in human classi- fication learning. This assumption holds that object feature values are statistically independent of each other, given knowl- edge of the object’s true category. Treating features as class- conditionally independent can in many situations substantially facilitate learning and categorization even if the assumption is not perfectly true. Using optimal experimental design princi- ples, we designed a task to test whether people have this de- fault assumption when learning to categorize. Results provide some supporting evidence, although the data are mixed. What is clear is that classification behavior adapts to the structure of the environment: a category structure that is unlearnable under the assumption of class-conditional independence is learned by all participants.

Jarecki, J., Meder, B., & Nelson, J. D. (2013). The assumption of class-conditional independence in category learning. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Cooperative minds: Social interaction and group dynamics. Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 2650-2655). Austin, TX: Cognitive Science Society. (Full text)

Publication year	2013
Document type:	In book
Publication status:	Published
External URL:	http://mindmodeling.org/cogsci2013/papers/0478/paper0478.pdf View
Categories:
Keywords:	multiple-cue classification learningcausal markov conditionclass-conditional independencenaive bayes