How causal knowledge affects classification: A generative theory of categorization.

How causal knowledge affects classification: A generative theory of categorization.

Several theories have been proposed regarding how causal relations among features of objects affect how those objects are classified. The assumptions of these theories were tested in 3 experiments that manipulated the causal knowledge associated with novel categories. There were 3 results. The 1st was a multiple cause effect in which a feature's importance increases with its number of causes. T...

Running Head: A Generative Theory of Categorization How Causal Knowledge Affects Classification: A Generative Theory of Categorization

Several theories have been proposed regarding how causal relations among features of objects affect how those objects are classified. The assumptions of these theories were tested in three experiments which manipulated the causal knowledge associated with novel categories. There were three results. The first was a multiple cause effect in which a feature’s importance increases with its number o...

A Causal-Model Theory of Categorization

In this article I propose that categorization decisions are often made relative to causal models of categories that people possess. According to this causal-model theory o f categorization, evidence of an exemplar's membership in a category consists of the likelihood that such an exemplar can be generated by the category's causal model. Bayesian networks are proposed as a representation of thes...

Running head: A Generative Theory of Classification Essentialism as a Generative Theory of Classification

Running head: Causal-Model Theory A Causal-Model Theory of Conceptual Representation and Categorization

This article presents a theory of categorization that accounts for the effects of causal knowledge that interrelates or links the features of categories. According to causal-model theory, people explicitly represent the probabilistic causal mechanisms that link category features, and classify objects by evaluating whether they were likely to have been generated by those mechanisms. Participants...