PMID: 12747507May 16, 2003

The multifaceted nature of unsupervised category learning

Psychonomic Bulletin & Review
Bradley C Love

Abstract

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.

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Related Concepts

Discrimination Learning
Pattern Recognition, Visual
Reaction Time
Problem Solving (Mental Process)
Probability Learning
Feedback - System Communication
Concept Formation
Learning Disorders
Color Perception
Psychophysics

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