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The Assumption of Class-conditional Independence in Category Learning

Jarecki, J, Meder, B and Nelson, JD (2013) The Assumption of Class-conditional Independence in Category Learning In: 35th Annual Meeting of the Cognitive Science Society, 2013-07-31 - 2013-08-03, Berlin, Germany.

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This paper investigates the role of the assumption of class-conditional independence of object features in human classification learning. This assumption holds that object feature values are statistically independent of each other, given knowledge 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 principles, we designed a task to test whether people have this default 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.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Psychology
Divisions : Surrey research (other units)
Authors :
Jarecki, J
Meder, B
Date : November 2013
Contributors :
Knauff, M
Sebanz, N
Pauen, M
Wachsmuth, I
publisherCognitive Science Society,
Uncontrolled Keywords : Multiple-cue classification learning, Class-conditional independence, Naıve Bayes, Causal Markov condition
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 10:48
Last Modified : 23 Jan 2020 16:14

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