Neural networks.
88 Citations•1995•
David Kriesel
Lancet
An overview of neural networks is provided, from a statistician's vantage point, why neural networks might be attractive and how they compare to other modern regression techniques.
Abstract
Arti cial neural networks are being used with increasing frequency for high dimensional problems of regression or classi cation. This article provides a tutorial overview of neural networks, focusing on back propagation networks as a method for approximating nonlinear multivariable functions. We explain, from a statistician's vantage point, why neural networks might be attractive and how they compare to other modern regression techniques.