Extremely randomized neural networks for constructing prediction intervals

The aim of this paper is to propose a novel prediction model based on an ensemble of deep neural networks adapting the extremely randomized trees method originally developed for random forests. The extra-randomness introduced in the ensemble reduces the variance of the predictions and improves out-o...

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Veröffentlicht in:	Neural networks 2021-12, Vol.144, p.113-128
Hauptverfasser:	Mancini, Tullio, Calvo-Pardo, Hector, Olmo, Jose
Format:	Artikel
Sprache:	eng
Schlagworte:	Dropout Ensemble methods Neural networks Prediction interval Uncertainty quantification
Online-Zugang:	Volltext
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