Learning representations by backpropagating errors
- D-E. Rumelhart, E. Hinton G, J. Willians R
- Computación y Sistemas, (Forthcoming),
In this work a method to facilitate the elaboration of a forecast for people with little statistical training is proposed. The method uses a rather simple yet sufficiently accurate time series characterization that allowed training a series of artificial neural networks (ANNs) to predict the forecasting performance of several statistical techniques. A case study is presented to demonstrate the application of the method. All techniques used, including the ANN, were conveniently coded in MS Excel so the computational requirements are modest. Furthermore, the results can be tabulated for quick consultation.