Anand, Sarabjot Singh, Patterson, D. and Hughes, J. G. (1998) Knowledge intensive exception spaces. In: 15th National Conference On Artificial intelligence (AAAI-98), 1998. Published in: Proceedings of the fifteenth national conference on artificial intelligence pp. 574-579. ISBN 9781577354185.

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Abstract

In this paper we extend the concept of exception spaces as defined by Cost and Salzberg (Cost and Salzberg, 1993), in the context of exemplar-based reasoning. Cost et al. defined exception spaces based on the goodness, in terms of performance, of an exemplar. While this is straightforward when using exemplars for classification problems, such a definition does not exist for regression problems. Thus, firstly we define a measure of goodness of an exemplar. We then use this measure of goodness to compare the effectiveness of exception spaces with a variant that we introduce, called Knowledge Intensive Exception Spaces or KINS. KINS remove the restriction on the geometric shape of exception spaces as defined by Cost et al. We provide a rationale for KINS and use a data set from the domain of colorectal cancer to support our hypothesis that KINS are a useful extension to exception spaces.

Item Type:	Conference Item (Paper)
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions:	Faculty of Science > Computer Science
Journal or Publication Title:	Proceedings of the fifteenth national conference on artificial intelligence
Publisher:	AAAI
ISBN:	9781577354185
Official Date:	1998
Dates:	Date Event 1998 Published
Page Range:	pp. 574-579
Status:	Peer Reviewed
Publication Status:	Published
Conference Paper Type:	Paper
Title of Event:	15th National Conference On Artificial intelligence (AAAI-98)
Type of Event:	Conference
Date(s) of Event:	1998
Related URLs:	Organisation

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