Speculative experiment with neural networks on separation and scoring in financial applications
Ilya Kogan · 1991
The difference between separation and scoring with neural networks is analyzed. This study was motivated by financial application of neural networks. A separation corollary is obtained: the better the separation in a BNN (backpropagation neural network) trained with a binary training file, the less the results may be used for scoring.>