Customization and Evaluation of Neural Networks in K-fold Cross-Validation in model screening platform
I need to use neural network modeling for predicting variables and to avoid overfitting, I'm utilizing the K-fold cross-validation method. On the model screening platform, the neural network is fitted using boosting with three TanH functions. Is it possible to customize the neural network by using a different number and configuration than the platform’s default settings? I need to obtain the R-squ...