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https://hdl.handle.net/2440/99355
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Type: | Journal article |
Title: | The helpfulness of category labels in semi-supervised learning depends on category structure |
Author: | Vong, W. Navarro, D. Perfors, A. |
Citation: | Psychonomic Bulletin and Review, 2016; 23(1):230-238 |
Publisher: | Springer |
Issue Date: | 2016 |
ISSN: | 1069-9384 1531-5320 |
Statement of Responsibility: | Wai Keen Vong, Daniel J. Navarro, Amy Perfors |
Abstract: | The study of semi-supervised category learning has generally focused on how additional unlabeled information with given labeled information might benefit category learning. The literature is also somewhat contradictory, sometimes appearing to show a benefit to unlabeled information and sometimes not. In this paper, we frame the problem differently, focusing on when labels might be helpful to a learner who has access to lots of unlabeled information. Using an unconstrained free-sorting categorization experiment, we show that labels are useful to participants only when the category structure is ambiguous and that people's responses are driven by the specific set of labels they see. We present an extension of Anderson's Rational Model of Categorization that captures this effect. |
Keywords: | Category learning computational modeling semi-supervised learning |
Rights: | © Psychonomic Society, Inc. 2015 |
DOI: | 10.3758/s13423-015-0857-9 |
Grant ID: | http://purl.org/au-research/grants/arc/FT110100431 http://purl.org/au-research/grants/arc/DE120102378 http://purl.org/au-research/grants/arc/DP110104949 |
Published version: | http://dx.doi.org/10.3758/s13423-015-0857-9 |
Appears in Collections: | Aurora harvest 7 Psychology publications |
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