Pattern Layer Reduction for a Generalized Regression Neural Network by Using a Self–Organizing Map

Pattern Layer Reduction for a Generalized Regression Neural Network by Using a Self–Organizing Map

In a general regression neural network (GRNN), the number of neurons in the pattern layer is proportional to the number of training samples in the dataset. The use of a GRNN in applications that have relatively large datasets becomes troublesome due to the architecture and speed required. The great...

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Bibliographic Details
Main Authors: Kartal Serkan, Oral Mustafa, Ozyildirim Buse Melis
Format: Article
Language:English
Published: Sciendo 2018-06-01
Series:International Journal of Applied Mathematics and Computer Science
Subjects:
generalized regression neural network
artificial neural network
self-organizing maps
nearest neighbour
reduced dataset
Online Access:https://doi.org/10.2478/amcs-2018-0031

Internet

https://doi.org/10.2478/amcs-2018-0031

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