hi guys, Im using a standard 'cross validation with SVM' scheme and want to get the predicted labels computed by the trained SVM on the test data set. How do I do that? Thanks! P.
0
Answers
IngoRMAdministrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Community Manager, RMResearcher, Member, University ProfessorPosts: 1,751 RM Founder
Hi,
simply replace the X-Validation operator by the operator X-Prediction. If you want both, predicted labels and estimated performance in a single run you would have to append the predictions after model application to a data set (via Remember, Recall, and Append or directly writing in a database for example).
How come the split validation operator can not return the labelled test set?
It only returns the full "data set". It does not return the part used for training and the part used for testing.
that is because the main purpose of that operator is validation, i.e. computation of the performance, not the model application - normally, you would want to get the performance as main output and not the example set.
Contributor I
Answers
simply replace the X-Validation operator by the operator X-Prediction. If you want both, predicted labels and estimated performance in a single run you would have to append the predictions after model application to a data set (via Remember, Recall, and Append or directly writing in a database for example).
Cheers,
Ingo
It only returns the full "data set". It does not return the part used for training and the part used for testing.
Kind regards,
Tobias