Title :
An oracle based on the general regression neural network
Author :
Masters, Timothy ; Land, Walker H., Jr. ; Maniccam, Suchindram
Author_Institution :
TMAIC, Vestal, NY, USA
Abstract :
The general regression neural network is well known to be an extremely effective prediction model in a wide variety of problems. It has been established that in many prediction problems, the results obtained by intelligently combining the outputs of several different prediction models are generally superior to the results obtained by using any one of the models. An overseer model that combines predictions from other independently trained prediction models is often called an oracle. The paper describes how the general regression neural network can be modified to serve as a powerful oracle for combining decisions from multiple arbitrary models
Keywords :
forecasting theory; neural nets; general regression neural network; oracle; overseer model; prediction model; recently; Density functional theory; Equations; Neural networks; Predictive models;
Conference_Titel :
Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4778-1
DOI :
10.1109/ICSMC.1998.728119