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Evaluation of Classification models
Muhammed_Fatih_
Member Posts: 93 
Maven
Hello together,
is there a possibility within RapidMiner to parallelly train and test selected classification models and subsequently return the best performance result of the respective classification model? The goal of my research is to evaluate the behaviour of classification models with regard to the determination of the best performance.
Thank you for your answers!
Best regards,
Fatih
is there a possibility within RapidMiner to parallelly train and test selected classification models and subsequently return the best performance result of the respective classification model? The goal of my research is to evaluate the behaviour of classification models with regard to the determination of the best performance.
Thank you for your answers!
Best regards,
Fatih
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Best Answer
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sgenzer
Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,959 
Community Manager
7
Answers
thank you for your answer which was very helpful
1. Inside AutoModel, by default, the model(s) is (are) not validated by a cross-validation, but by a multi - hold-out-set validation.
See the documentation on the "results" screen :
You can also inspect the generated process(es) after executing AutoModel to inspect them and understand exactly how is (are)
calculated the performance of the model(s).
2. If you want to obtain the comparaison of ROC curves with a cross-validation, you can use the Compare ROCs operator.
Simply put the models you want to benchmark inside this operator.
Hope this helps,
Regards,
Lionel