Experimenting with artificial neural networks-artificial intelligence mini-tutorial. 3

For pt.1 see ibid., p.33-42; for pt.2 see ibid., p.43-4. To show how neural nets work, experiences in an experiment using them are described. The experiment involves using AI techniques to assist in the discovery of causal relationships between the variables existing in a large clinical trial database. A peripheral vascular disease database was used to acquire a feeling for the complexities involved in developing a distributed encoding scheme and to determine the computational resources required to train a neural net for the type of data used. By testing several models the effects of changes in the encoding scheme and the number of training iterations the system needed to predict the appropriate change needed could be determined. These results were compared to the information available from other analyses of the same data. The generative capabilities of the system were then tested by training it over one sample of cases and applying it to cases it had not encountered before. Some idea of the computational resources needed in terms of time and memory capacity was developed