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A New Weighted k-Nearest Neighbor Algorithm Based on Newton¿s Gravitational Force

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A New Weighted k-Nearest Neighbor Algorithm Based on Newton¿s Gravitational Force

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Aguilera, J.; González, LC.; Montes-Y-Gómez, M.; Rosso, P. (2019). A New Weighted k-Nearest Neighbor Algorithm Based on Newton¿s Gravitational Force. Lecture Notes in Computer Science. 11401:305-313. https://doi.org/10.1007/978-3-030-13469-3_36

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/159134

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Title: A New Weighted k-Nearest Neighbor Algorithm Based on Newton¿s Gravitational Force
Author: Aguilera, Juan González, Luis C. Montes-y-Gómez, Manuel Rosso, Paolo
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
[EN] The kNN algorithm has three main advantages that make it appealing to the community: it is easy to understand, it regularly offers competitive performance and its structure can be easily tuning to adapting to the needs ...[+]
Subjects: KNN , Newton's gravitational force
Copyrigths: Reserva de todos los derechos
Source:
Lecture Notes in Computer Science. (issn: 0302-9743 )
DOI: 10.1007/978-3-030-13469-3_36
Publisher:
Springer-Verlag
Publisher version: https://doi.org/10.1007/978-3-030-13469-3_36
Conference name: 23rd Iberoamerican Congress on Pattern Recognition (CIARP 2018)
Conference place: Madrid, Spain
Conference date: Noviembre 19-22,2018
Project ID:
CONACYT/FC 2016-2410
MINISTERIO DE ECONOMIA Y EMPRESA/TIN2015-71147-C2-1-P
Thanks:
This research was partially supported by CONACYT-Mexico (project FC-2410). The work of Paolo Rosso has been partially funded by the SomEMBED TIN2015-71147-C2-1-P MINECO research project.
Type: Artículo Comunicación en congreso Capítulo de libro

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