Combining Cross-Validation and Ensemble Creation for Artificial Neural Networks
Artificial neural networks (ANNs) are widely used nowadays, and the research into improving their performances is continually ongoing. One main goal of ANNs is to have a high generalization performance, which can be estimated through validation. Ensembles can be useful to raise the generalization performance, but the validation of ensembles is often computationally costly if the size of the traini
