Pattern layer reduction for a generalized regression neural network by using a self-organizing map - Kartal, Serkan; Oral, Mustafa; Ozyildirim, Buse Melis (Zielona Góra: Uniwersytet Zielonogórski)
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 number of neurons in the pattern layer requires a substantial increase in memory usage and causes a substantial decrease in calculation speed.
Keywords: generalized regression neural network; artificial neural networks; self-organizing maps; nearest neighbour; reduced dataset