2026-09-15T18:15:39Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1344752025-04-30T20:37:35Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134243
Gestión del Repositorio Documental de la Universidad de Salamanca
author
Colin, Fyfe
author
Corchado Rodríguez, Juan Manuel
2017-09-05T11:02:32Z
2017-09-05T11:02:32Z
2001
International Journal of Intelligent Systems. Volumen 16 (4), pp. 571-586. Wiley-Blackwell.
0884-8173 (Print) / 1098-111X (Online)
http://hdl.handle.net/10366/134475
Instance-based reasoning systems and, in general, case-based reasoning systems are normally used in problems for which it is difficult to define rules. Although case-based reasoning methods have proved their ability to solve different types of problems, there is still a demand for methods that facilitate their automation during their creation and the retrieval and reuse stages of their reasoning circle. This paper presents one method based on kernels, which can be used to automate some of the reasoning steps of instance-based reasoning systems. Kernels were originally derived in the context of support vector machines, which identify the smallest number of data points necessary to solve a particular problem (e.g., regression or classification). Unsupervised kernel methods have been used successfully to identify the optimal instances to instantiate an instance base. The efficiency of the kernel model is shown on an oceanographic problem. © 2001 John Wiley & Sons, Inc.
en
Attribution-NonCommercial-NoDerivs 3.0 Unported
Computer Science
Automating the construction of CBR systems using kernel methods
info:eu-repo/semantics/article
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URL
https://gredos.usal.es/bitstream/10366/134475/1/2001_rev_ijis_006.pdf
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2001_rev_ijis_006.pdf
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2001_rev_ijis_006.pdf.txt