cross validation
Hi
I have a cross validation set up with a gradient boosted tree model in it. In the test piece, I apply the model and the performance is sent to a performance operator. The outcome matrix counts the same nr of records as what I fed into the cross validation. Is this normal?
I have a cross validation set up with a gradient boosted tree model in it. In the test piece, I apply the model and the performance is sent to a performance operator. The outcome matrix counts the same nr of records as what I fed into the cross validation. Is this normal?
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Clear! Thank you Varun
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Hello @Joos
It is normal. CV uses all the data in both training and testing, the fold number creates subsets of data to train and test in each fold. The final performance is aggregate of all folds.
Here is a detailed explanation of CV.
https://community.rapidminer.com/discussion/54621/cross-validation-and-its-outputs-in-rm-studio
Best
Varun
It is normal. CV uses all the data in both training and testing, the fold number creates subsets of data to train and test in each fold. The final performance is aggregate of all folds.
Here is a detailed explanation of CV.
https://community.rapidminer.com/discussion/54621/cross-validation-and-its-outputs-in-rm-studio
Best
Varun
It is normal. CV uses all the data in both training and testing, the fold number creates subsets of data to train and test in each fold. The final performance is aggregate of all folds.
Here is a detailed explanation of CV.
https://community.rapidminer.com/discussion/54621/cross-validation-and-its-outputs-in-rm-studio
Best
Varun