Cross-validation, it’s a model validation techniques for assessing how the results of a statistical analysis (model) will generalize to an independent data set
Before of course you split entire data set in 75% for training 25% for evaluation both randomly , train the net on the 75% and evaluate on the rest of 25% . IMPORANT AFTER DID THIS DELETE NEWORK MODEL. Repeat all 10 times
Alexandru Daia, I divided the data set as I mentioned using Matlab program and I applied the method crosse validation after that and before I use the model neuronal but it did not give me any result and did not show that there is an error