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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

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Accepted answers

sgenzer

Hello @Muhammed_Fatih_ absolutely. It's called "Auto Model" and it's at the top of your screen.

Image: https://us.v-cdn.net/6030995/uploads/editor/je/eownob42f8ny.png

All comments

sgenzer

Hello @Muhammed_Fatih_ absolutely. It's called "Auto Model" and it's at the top of your screen.

Muhammed_Fatih_

Hi @sgenzer,

thank you for your answer which was very helpful

Is there also the possibility to execute ROC Comparison with Cross-Validation?

lionelderkrikor

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 :

Image: https://us.v-cdn.net/6030995/uploads/editor/zx/s2h0w7sz4uia.png

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