Global and local neural network ensembles
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
Elsevier BVDate
1998-07-06Citation
10.1016/S0167-8655(98)00042-7
Pattern Recognition Letters 19.8 (1998): 651 – 655
ISSN
0167-8655 (print); 1872-7344 (online)DOI
10.1016/S0167-8655(98)00042-7Editor's Version
http://dx.doi.org/10.1016/S0167-8655(98)00042-7Subjects
Neural Network Ensemble; Global Neural Network; Local Neural Network; Handwritten Digit Recognition; InformáticaNote
This is the author’s version of a work that was accepted for publication in Pattern Recognition Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pattern Recognition Letters, 19, 8, (1998) DOI: 10.1016/S0167-8655(98)00042-7Rights
© 1998 Elsevier B.V. All rights reservedEsta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional.
Abstract
Surprisingly simple local learning algorithms are known to outperform many other global non linear machines Unfortunately these algorithms are computationally costly A means of assembling both learning ap proaches is proposed in this letter and shown to enhance performance
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Google Scholar:Sierra Urrecho, Alejandro
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Santa Cruz Fernández, Carlos
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