We introduce the chi-square test neural network: a single hidden layer
backpropagation neural network using chi-square test theorem to redefine the
cost function and the error function. The weights and thresholds are modified
using standard backpropagation algorithm...
The proposed approach has the
advantage of making consistent data distribution over training and testing
sets. It can be used for binary classification. The experimental results on
real world data sets indicate that the proposed algorithm can significantly
improve the classification accuracy comparing to related approaches.