The multifaceted nature of unsupervised category learning.
A substantial portion of category-learning research has focused on one learning mode--namely, classification learning (a supervised learning mode). Subsequently, theories of category learning have focused on how the abstract structure of categories (i.e., the co-occurrence patterns of feature values) affects acquisition. Recent work in supervised learning has shown that a learner's interactions with the stimulus set also plays an important role in acquisition. The present study extends this work to unsupervised learning situations involving simple one-dimensional stimuli. The results suggest that categorization performance is a function of both learning mode (i.e., study conditions) and learning problem (i.e., category structure). Unsupervised learning, like supervised learning, appears to be multifaceted, with different learning modes best paired with certain learning problems.
Department of Psychology, University of Texas, Austin, Texas 78712, USA. love@psy.utexas.edu
Bradley C
BC
Love
D000328:Adult; D001288:Attention; D003118:Color Perception; D003210:Concept Formation; D004193:Discrimination Learning; D005246:Feedback; D005260:Female; D006801:Humans; D008297:Male; D009949:Orientation; D010364:Pattern Recognition, Visual; D011337:Probability Learning; D011340:Problem Solving; D011597:Psychomotor Performance; D011601:Psychophysics; D011930:Reaction Time; D017603:Signal Detection, Psychological