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Abstract: OF THE DISSERTATION Concept-Learning in the Absence of Counter-Examples: An Autoassociation-Based Approach to Classification by Nathalie Japkowicz Dissertation Directors: Stephen Jos'e Hanson and Casimir Kulikowski The overwhelming majority of research currently pursued within the framework of concept-learning concentrates on discrimination-based learning, an inductive learning paradigm that relies on both examples and counter-examples of the concept. This emphasis, however, can present a... (Update)
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...of this analysis, and it concludes with a discussion of our results. Section 4 summarizes our findings. Additional details can be found in [3]. 1 Another interesting aspect of this dichotomy is that the recognition based system can be significantly more accurate than the...
...Such data 12 We would like to thank Gary Cottrell for suggesting this comparison. 13 Support for this speculation can be found in [Japkowicz1999] which shows a clear decrease in classification accuracy by NL NL as the conceptual clusters of the domain in Figure 1(c) are moved...
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BibTeX entry: (Update)
Nathalie Japkowicz. ConceptLearning in the Absence of Counter-Examples: An Autoassociation-Based Approach to Classification (in progress). PhD thesis, Rutgers University, 1999. http://citeseer.ist.psu.edu/japkowicz99conceptlearning.html More
@misc{ japkowicz99conceptlearning,
author = "N. Japkowicz",
title = "ConceptLearning in the Absence of Counter-Examples: An Autoassociation-Based
Approach to Classification",
text = "Nathalie Japkowicz. ConceptLearning in the Absence of Counter-Examples:
An Autoassociation-Based Approach to Classification (in progress). PhD thesis,
Rutgers University, 1999.",
year = "1999",
url = "citeseer.ist.psu.edu/japkowicz99conceptlearning.html" }
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