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Using proximity and spatial homogeneity in neighbourhood-based classifiers

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (1997) 1310 206-213
DOI: 10.1007/3-540-63507-6_203
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Abstract

In this paper, a set of neighbourhood-based classifiers are jointly used in order to select a more reliable neighbourhood of a given sample and take an appropriate decision about its class membership. The approaches introduced here make use of two concepts: proximity and symmetric placement of the samples.

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Sánchez, J. S., Pla, F., & Ferri, F. J. (1997). Using proximity and spatial homogeneity in neighbourhood-based classifiers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1310, pp. 206–213). Springer Verlag. https://doi.org/10.1007/3-540-63507-6_203

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