RELATION BETWEEN THE RATIONAL MODEL AND THE CONTEXT MODEL OF CATEGORIZATION (original) (raw)

Comparing Categorization Models

Journal of Experimental Psychology: General, 2004

Four experiments are presented that competitively test rule-and exemplar-based models of human categorization behavior. Participants classified stimuli that varied on a unidimensional axis into 2 categories. The stimuli did not consistently belong to a category; instead, they were probabilistically assigned. By manipulating these assignment probabilities, it was possible to produce stimuli for which exemplar-and rule-based explanations made qualitatively different predictions.F. G. Ashby and J. T. Townsend's (1986) rule-based general recognition theory provided a better account of the data than R. M. Nosofsky's (1986) exemplar-based generalized context model in conditions in which the to-be-classified stimuli were relatively confusable. However, generalized context model provided a better account when the stimuli were relatively few and distinct. These findings are consistent with multiple process accounts of categorization and demonstrate that stimulus confusion is a determining factor as to which process mediates categorization.

Thirty categorization results in search of a model

Journal of Experimental Psychology: …, 2000

(2000) conducted a meta-analysis of 30 data sets reported in the classification literature that involved use of the "5-4" category structure introduced by D. L. Medin and M. M. Schaffer (1978). The meta-analysis was aimed at investigating exemplar and elaborated prototype models of categorization. In this commentary, the author argues that the meta-analysis is misleading because it includes many data sets from experimental designs that are inappropriate for distinguishing the models. Often, the designs involved manipulations in which the actual 5-4 structure was not, in reality, tested, voiding the predictions of the models. The commentary also clarifies various aspects of the workings of the exemplar-based context model. Finally, concerns are raised that the all-or-none exemplar processes that form part of Smith and Minda's (2000) elaborated prototype models are implausible and lacking in generality.

A Causal-Model Theory of Conceptual Representation and Categorization

Journal of Experimental Psychology: Learning, Memory, and Cognition, 2003

This article presents a theory of categorization that accounts for the effects of causal knowledge that relates 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. In 3 experiments, participants were taught causal knowledge that related the features of a novel category. Causal-model theory provided a good quantitative account of the effect of this knowledge on the importance of both individual features and interfeature correlations to classification. By enabling precise model fits and interpretable parameter estimates, causal-model theory helps place the theory-based approach to conceptual representation on equal footing with the well-known similarity-based approaches.

Unifying rational models of categorization via the hierarchical Dirichlet process

Proceedings of the 29th annual conference of the cognitive science society, 2007

Models of categorization make different representational assumptions, with categories being represented by prototypes, sets of exemplars, and everything in between. Rational models of categorization justify these representational assumptions in terms of different schemes for estimating probability distributions. However, they do not answer the question of which scheme should be used in representing a given category. We show that existing rational models of categorization are special cases of a statistical model called ...

Two mathematical models of human categorization

The goal of the paper is mathematical verification of various hypotheses concerning the cognitive efficiency of human categorization. To this aim two calculus-based mathematical models are constructed to account for the crucial features of human categorization: prototypicality and basic level primacy. The first model allows to calculate and compare the cognitive efficiency of the prototype and definition based categories, while the second one explicates the cognitive prominence of the basic level categories. Additionally, the models account for cultural and specialist knowledge variability of categorization as well as the link between the limited human brain capacity and categorization. Both models can be also be used to predict and extrapolate the results of psycho-linguistic experiments.

Family resemblances: Studies in the internal structure of categories

Cognitive Psychology, 1975

Six experiments explored the hypothesis that the members of categories which are considered most prototypical are those with most attributes in common with other members of the category and least attributes in common with other categories. In probabilistic terms, the hypothesis is that prototypicality is a function of the total cue validity of the attributes of items. In Experiments 1 and 3, subjects listed attributes for members of semantic categories which had been previously rated for degree of prototypicality.

The conceptual base view of categorization

Journal of Psycholinguistic Research, 1985

An experiment was designed to show that some categories, called Type C categories, are mediated by an abstract, interpretively derived conceptual base. To this end, each of four groups of subjects ranked 10 sentences (instances) in terms of how well they illustrated the figurative meaning of a proverb (Proverb group), or how well they illustrated the meaning of an excellent interpretation of the proverb (Excellent Interpretation group), or a poor interpretation of the proverb (Poor Interpretation group), or an unspecified, unstated underlying meaning (Control group). The Excellent Interpretation groups' rankings correlated highly with standard ranks established by the Proverb group, but the Poor Interpretation group's and the Control group's ranking were uncorrelated with these two group's rankings. Apparently, the subjects in the Proverb group accomplished their rankings by using a conceptual base or microtheory similar in meaning to the interpretation used by the Excellent Interpretation group. Discussion centered on the question of whether the Classical, Probabilistic, or Exemplar Views of categorization (Smith & Medin, 1981) could account for the results. It was argued that they could not, basically because Type C categories are more dependent upon interpretive processes than the more perceptually based Type P categories to which these views have traditionally been applied.