Interval-based neural networks for soft decisions
Patricia Nava · 2002
The performance of neural networks, when the training data is limited, can be improved by incorporation of interval techniques. These techniques improve performance by introducing the ability to classify imprecise data. Performance can be further improved by incorporating the ability to make soft decisions. Soft decisions differ from hard decisions by allowing the decision-making system the option of deferring to a human. This decision-rejection option has the effect of reducing the error rate of the decision-making system. The paper discusses three distinct techniques for making soft decisions and the performance of the interval-based neural network that utilizes these techniques.