Two experiments investigated category inference when categories were composed of correlated or uncorrelated dimensions and the categories overlapped minimally or moderately. When the categories minimally overlapped, the dimensions were strongly correlated with the category label. Following a classification learning phase, subsequent transfer required the selection of either a category label or a feature when one, two, or three features were missing. Experiments 1 and 2 differed primarily in the number of learning blocks prior to transfer. In each experiment, the inference of the category label or category feature was influenced by both dimensional and category correlations, as well as their interaction. The number of cues available at test impacted performance more when the dimensional correlations were zero and category overlap was high. However, a minimal number of cues were sufficient to produce high levels of inference when the dimensions were highly correlated; additional cues had a positive but reduced impact, even when overlap was high. Subjects were generally more accurate in inferring the category label than a category feature regardless of dimensional correlation, category overlap, or number of cues available at test. Whether the category label functioned as a special feature or not was critically dependent upon these embedded correlations, with feature inference driven more strongly by dimensional correlations.Keywords Categorization . Concepts . Inductive reasoning . Expertise . MemoryThe experimental study of human categories has an extensive history, beginning with the seminal study of Hull (1920) and continuing today into the identification of variables critical to the shaping of concepts and the development of formal, quantitative models of classification.Hull introduced the classification paradigm that dominates most current research today. In this paradigm, the subject initially assigns a number of patterns into designated categories, followed by a transfer test containing old and new instances. By manipulation of variables in the learning phase and then evaluating transfer performance, Hull was able to draw a number of conclusions about the learning and representation of concepts; for example, concepts were learned more rapidly in the order from simple to complex rather than the reverse, transfer was better following learning of many patterns shown infrequently rather than a few patterns presented numerous times, and so forth.However, categories provide functions above and beyond classification. Bruner, Goodnow, and Austin (1966) summarized a number of additional utilities of categories: Once learned, they permit generalization to novel instances, thereby reducing the need for new learning; they simplify the incredible complexity of the environment into a manageable set of units, thereby facilitating a host of cognitive functions, including logical reasoning and communication; they are adaptive so that harmful or threatening stimuli can be responded to appropriately; and they permit i...