Learning the correlational structure of stimuli in a one-attribute classification task

Autor:	Serge Larochelle, Gyslain Giguère, Guy L. Lacroix
Rok vydání:	2007
Předmět:	business.industry Concept learning Variable and attribute Experimental and Cognitive Psychology Test phase Artificial intelligence Stimulus (physiology) Psychology business computer.software_genre Social psychology computer Natural language processing
Zdroj:	European Journal of Cognitive Psychology. 19:457-469
ISSN:	1464-0635 0954-1446
DOI:	10.1080/09541440600926716
Popis:	In category learning experiments, participants typically do not learn within-category correlations unless the composition of the categories or the task demands compel them to do so. To determine if correlations among attributes could be learned without explicitly focusing the participants’ attention on them, a task was designed that allowed stimuli to be classified on the basis of a single perfectly predictive attribute. Each training stimulus also included attributes that were either perfectly or partly correlated with the rule attribute. Then, in a test phase, the impact of eliminating the rule attribute on classification was evaluated. The experiment showed that some of the attributes that were perfectly correlated with the rule attribute were learned. These attributes could be used to classify the test exemplars even though the rule attribute had been removed. This experiment provides evidence that within-category correlations can be learned incidentally during classification tasks.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::3daad7e6bdda6d2151a3de835fe2e0b7 https://doi.org/10.1080/09541440600926716 Zobrazit plný text záznamu