Improving the Accuracy of Nearest-Neighbor Classification Using Principled Construction and Stochastic Sampling of Training-Set Centroids

A conceptually simple way to classify images is to directly compare test-set data and training-set data. The accuracy of this approach is limited by the method of comparison used, and by the extent to which the training-set data cover configuration space. Here we show that this coverage can be subst...

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Detalles Bibliográficos
Autor principal: Whitelam, Stephen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7911166/
https://www.ncbi.nlm.nih.gov/pubmed/33530507
http://dx.doi.org/10.3390/e23020149

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7911166/
https://www.ncbi.nlm.nih.gov/pubmed/33530507
http://dx.doi.org/10.3390/e23020149

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