Performance of artificial neural network (ANN),
one of the useful tools used for credit scoring models, is
increased by proposed methodology in present study. Whereas
reducing the rate of error, in order to obtaining the best
possible result, and optimal network of ANN are very
important, in this paper, for reducing the errors of the artificial
neural networks, voting algorithm will be offered. Using
mentioned algorithm, the outputs of ANN , are categorized in
three different groups and according to the taken results,
these algorithms have the ability to reduce the resulted errors
of the best made model of the neural networks in a value of
1.03 percent.
