Thanks for your input.
My question is I want to use the trained NN model to forecast with the dataset that was not used in training or testing.
I believe this data needs to be normalized too, but how should it be done? And what about the final predict from this process especially taking the data back to normal predicted values.
predict_testNN = compute(NN, testNN[,c(1:5)])
This testNN was used in the normalization process. Now assume it is new dataset mydata with 1:5 columns. How is the normalization be done on this?
After then what about the prediction over here (Something like this below) will it be the same or will change? if yes how?
predict_testNN = (predict_testNN$net.result * (max(data$rating) - min(data$rating))) + min(data$rating)
Hope now it is well understood.