title: Combining logistic regression and neural networks to create predictive models.
abstract: Neural networks are being used widely in medicine and other areas to create predictive models from data. The statistical method that most closely parallels neural networks is logistic regression. This paper outlines some ways in which neural networks and logistic regression are similar, shows how a small modification of logistic regression can be used in the training of neural network models, and illustrates the use of this modification for variable selection and predictive model building with neural networks.
authors: Biomedical Information Communication Center, Oregon Health Sciences University, Portland.
authors: K A
authors: KA
authors: Spackman
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D016571:Neural Networks, Computer; D012044:Regression Analysis