Refereed full papers (journals, book chapters, international conferences)

1994

@inproceedings{Sar1994,
	vgclass =	{refpap},
	vgproject =	{nn},
	author =	{Warren S. Sarle},
	title =	{Neural Networks and Statistical Models},
	booktitle =	{Proceedings of the Nineteenth Annual SAS Users Group
	International Conference},
	address =	{Cary, NC, USA},
	pages =	{1538--1550},
	publisher =	{SAS Institute},
	month =	{April},
	year =	{1994},
	abstract =	{There has been much publicity about the ability of
	artificial neural networks to learn and generalize. In fact, the most
	commonly used artificial neural networks, called multilayer
	perceptrons, are nothing more than nonlinear regression and
	discriminant models that can be implemented with standard statistical
	software. This paper explains what neural networks are, translates
	neural network jargon into statistical jargon, and shows the
	relationships between neural networks and statistical models such as
	generalized linear models, maximum redundancy analysis, projection
	pursuit, and cluster analysis.},
}