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Do Additional Features Help or Hurt Category Learning? The Curse of Dimensionality in Human Learners
Vong, Wai Keen; Hendrickson, Andrew T.; Navarro, Danielle J.; Perfors, Amy – Cognitive Science, 2019
The curse of dimensionality, which has been widely studied in statistics and machine learning, occurs when additional features cause the size of the feature space to grow so quickly that learning classification rules becomes increasingly difficult. How do people overcome the curse of dimensionality when acquiring real-world categories that have…
Descriptors: Learning Processes, Classification, Models, Performance
Kurtz, Kenneth J.; Honke, Garrett – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2020
A fundamental goal in the study of human cognition is to understand the transfer of knowledge. This goes hand-in-hand with the translational goal of promoting such transfer via instructional techniques. Despite a rich history of research using the analogical problem-solving paradigm, no study activity has been found to produce a robust rate of…
Descriptors: Transfer of Training, Concept Formation, Classification, Experiments
Vogel, Tobias; Carr, Evan W.; Davis, Tyler; Winkielman, Piotr – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
Stimuli that capture the central tendency of presented exemplars are often preferred--a phenomenon also known as the classic beauty-in-averageness effect. However, recent studies have shown that this effect can reverse under certain conditions. We propose that a key variable for such ugliness-in-averageness effects is the category structure of the…
Descriptors: Interpersonal Attraction, Preferences, Stimuli, Experiments
Cao, Rui; Nosofsky, Robert M.; Shiffrin, Richard M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2017
In short-term-memory (STM)-search tasks, observers judge whether a test probe was present in a short list of study items. Here we investigated the long-term learning mechanisms that lead to the highly efficient STM-search performance observed under conditions of consistent-mapping (CM) training, in which targets and foils never switch roles across…
Descriptors: Short Term Memory, Recall (Psychology), Item Response Theory, Learning Processes
Moreton, Elliott; Pater, Joe; Pertsova, Katya – Cognitive Science, 2017
Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by…
Descriptors: Phonology, Concept Formation, Learning Processes, Difficulty Level
Ashby, F. Gregory; Vucovich, Lauren E. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how…
Descriptors: Feedback (Response), Classification, Learning Processes, Associative Learning
Haskell, Todd R.; Mansfield, Cade D.; Brewer, Katherine M. – Language and Cognitive Processes, 2011
Several psycholinguistic theories have appealed to the linguistic notion of markedness to help explain asymmetrical patterns of behavioural data. We suggest that this sort of markedness is best thought of as a derived rather than a primitive notion, emerging when the distributional properties of linguistic categories interact with general-purpose…
Descriptors: Linguistics, Vocabulary Development, Classification, Learning Processes
Ye, Qiang – ProQuest LLC, 2010
Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…
Descriptors: Error Patterns, Classification, Learning Processes, Task Analysis
Rehder, Bob; Kim, ShinWoo – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2010
Research has documented two effects of interfeature causal knowledge on classification. A "causal status effect" occurs when features that are causes are more important to category membership than their effects. A "coherence effect" occurs when combinations of features that are consistent with causal laws provide additional…
Descriptors: Classification, Probability, Experiments, Experimental Psychology
Blair, Mark R.; Watson, Marcus R.; Walshe, R. Calen; Maj, Fillip – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2009
Humans have an extremely flexible ability to categorize regularities in their environment, in part because of attentional systems that allow them to focus on important perceptual information. In formal theories of categorization, attention is typically modeled with weights that selectively bias the processing of stimulus features. These theories…
Descriptors: Attention, Classification, Visual Perception, Experiments
Son, Ji Y.; Smith, Linda B.; Goldstone, Robert L. – Cognition, 2008
Development in any domain is often characterized by increasingly abstract representations. Recent evidence in the domain of shape recognition provides one example; between 18 and 24 months children appear to build increasingly abstract representations of object shape [Smith, L. B. (2003). Learning to recognize objects. "Psychological…
Descriptors: Generalization, Child Development, Experiments, Toddlers
Goschke, Thomas; Bolte, Annette – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2007
Through the use of a new serial naming task, the authors investigated implicit learning of repeating sequences of abstract semantic categories. Participants named objects (e.g., table, shirt) appearing in random order. Unbeknownst to them, the semantic categories of the objects (e.g., furniture, clothing) followed a repeating sequence.…
Descriptors: Semantics, Learning Processes, Language Processing, Experiments
Johansen, Mark K.; Kruschke, John K. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2005
This research's purpose was to contrast the representations resulting from learning of the same categories by either classifying instances or inferring instance features. Prior inference learning research, particularly T. Yamauchi and A. B. Markman (1998), has suggested that feature inference learning fosters prototype representation, whereas…
Descriptors: Inferences, Learning Processes, Classification, Models
Hoffman, Aaron B.; Murphy, Gregory L. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2006
Three experiments compared the learning of lower-dimensional family resemblance categories (4 dimensions) with the learning of higher-dimensional ones (8 dimensions). Category-learning models incorporating error-driven learning, hypothesis testing, or limited capacity attention predict that additional dimensions should either increase learning…
Descriptors: Experiments, Classical Conditioning, Probability, Comparative Analysis
SEIBEL, ROBERT – 1967
GIVEN THE TASK OF LEARNING A SERIES OF RANDOMLY ORDERED MEANINGFUL ITEMS, MOST SUBJECTS (SS) IMPOSE SOME ORGANIZATION ON THE MATERIAL DURING THE PROCESS OF LEARNING. AN EXPERIMENTAL PARADIGM IS DESCRIBED WHICH PERMITS THE OBJECTIVE SCORING OF EACH S'S SUBJECTIVE ORGANIZATION OF THE MATERIAL ON EACH LEARNING TRIAL. THE CENTRAL FEATURE OF THE…
Descriptors: Associative Learning, Classification, Cognitive Processes, Experiments