Evaluation of Classification models
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
Find more posts tagged with
Sort by:
1 - 3 of
31
Altair EmployeeHello @Muhammed_Fatih_ absolutely. It's called "Auto Model" and it's at the top of your screen. 
Hi @sgenzer,
thank you for your answer which was very helpful Is there also the possibility to execute ROC Comparison with Cross-Validation?
thank you for your answer which was very helpful
Is there also the possibility to execute ROC Comparison with Cross-Validation? 
Hi @Muhammed_Fatih_,
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
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
Sort by:
1 - 1 of
11
Altair Employee