Apply Model in RapidMiner

HeikoeWin786

Dear all,

I split a dataset 75%(Training) and 25%(Testing). I pre-processed the data on training data. Then, I split the training data again (75%-25%) and perform Naive Bayes Classification. I saved the model as a result of training data. 
However, if I want to test whether my model is applicable or not, I believe I need to run my model on the 25% which I kept as the test data initially. 
Means, for 25% of initial testing data, I will perform pre-processing same as training, then, I retrieve the pre-processed test data and apply the model which I saved from the training data. 
Could you please advise if this is correct or am I doing wrong here?

thanks.
Heikoe

Telcontar120

That would be correct, if you want to run split validation manually, which it sounds like you did.
You could also use the Split Validation operator, which does this automatically and delivers the performance on the test portion of the data.
But I would really recommend using Cross Validation instead, which will train and test on multiple subsets of your original data and supply the resulting validation performance automatically.