Category inference as a function of correlational structure, category discriminability, and number of available cues

[1]  Vladimir M Sloutsky,et al.  Carrot Eaters or Moving Heads , 2012, Psychological science.

[2]  Brian H. Ross,et al.  Classification versus inference learning contrasted with real-world categories , 2011, Memory & cognition.

[3]  Yasuaki Sakamoto,et al.  Learning and retention through predictive inference and classification. , 2010, Journal of experimental psychology. Applied.

[4]  B. Ross,et al.  Category vs. Object Knowledge in Category-based Induction. , 2010, Journal of memory and language.

[5]  S. Gelman,et al.  Five-year-olds’ beliefs about the discreteness of category boundaries for animals and artifacts , 2009, Psychonomic bulletin & review.

[6]  B. Rehder,et al.  Classification as Diagnostic Reasoning , 2022 .

[7]  Daniel R. Little,et al.  Better learning with more error: probabilistic feedback increases sensitivity to correlated cues in categorization. , 2009, Journal of experimental psychology. Learning, memory, and cognition.

[8]  S. Waxman,et al.  Early word-learning entails reference, not merely associations , 2009, Trends in Cognitive Sciences.

[9]  F Gregory Ashby,et al.  The effects of category overlap on information-integration and rule-based category learning , 2006, Perception & psychophysics.

[10]  S. Gelman.  Psychological essentialism in children , 2004, Trends in Cognitive Sciences.

[11]  Seth Chin-Parker,et al.  The effect of category learning on sensitivity to within-category correlations , 2002, Memory & cognition.

[12]  D. Homa,et al.  Recognition of Facial Prototypes: The Importance of Categorical Structure and Degree of Learning☆ , 2001 .

[13]  J A Swets,et al.  Psychological Science Can Improve Diagnostic Decisions , 2000, Psychological science in the public interest : a journal of the American Psychological Society.

[14]  Patricia M. Berretty,et al.  On the dominance of unidimensional rules in unsupervised categorization , 1999, Perception & psychophysics.

[15]  A. Markman,et al.  Category Learning by Inference and Classification , 1998 .

[16]  G. Murphy,et al.  Induction and category coherence , 1996, Psychonomic bulletin & review.

[17]  D. Homa,et al.  Influence of manipulated category knowledge on prototype classification and recognition , 1993, Memory & cognition.

[18]  Donald Homa,et al.  Abstraction of ill-defined form. , 1978 .

[19]  D. Homa,et al.  Integrative and metric properties of abstracted information as a function of category discriminability, instance variability, and experience. , 1977 .

[20]  M. Posner,et al.  Retention of Abstract Ideas. , 1970 .

[21]  M. Posner,et al.  On the genesis of abstract ideas. , 1968, Journal of experimental psychology.

[22]  William M. Smith,et al.  A Study of Thinking , 1956 .

[23]  A. Markman,et al.  Inference using categories. , 2000, Journal of experimental psychology. Learning, memory, and cognition.

[24]  James F. Knutson,et al.  Unsupervised Concept Learning and Value Systematicity: A Complex Whole Aids Learning the Parts , 1996 .

[25]  Gregory L. Murphy,et al.  Feature correlations in conceptual representations , 1989 .

[26]  D. Homa.  On the Nature of Categories , 1984 .

[27]  Mark W. Altom,et al.  Correlated symptoms and simulated medical classification. , 1982, Journal of experimental psychology. Learning, memory, and cognition.

[28]  Daniel F. Chambliss,et al.  Evolution of conceptual structure , 1979 .

[29]  C. L. Hull.  Quantitative aspects of evolution of concepts: An experimental study. , 1920 .