What model comes out of X-Validation?

Fred12Fred12 Member Posts: 344 Unicorn
edited November 2018 in Help


I'd like to know what is the model that is going out of X-Validation? is it the model with the best performance, or just the last model? because in 10-fold X-Validation u have 10 models at the end...

furthermore, the same I would like to know from which model the contingency-table is at the output at the end.. is it from the last model, the best model ? because I guess it cannot be the average of all contingency tables... ;)

Best Answers

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    IngoRMIngoRM Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Community Manager, RMResearcher, Member, University Professor Posts: 1,751 RM Founder
    Solution Accepted

    Tom is right, it is the model built on the entire data set.  Here is probably a useful discussion which will answer a lot of the question you most likely will have very soon (well, predicting the future is part of our business :smileywink: )




    Hope this helps,


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    Fred12Fred12 Member Posts: 344 Unicorn
    Solution Accepted

    ok but I still don't understand how it can be the model that is trained on all the dataset, if we are only training on parts of the dataset... 

    how is the final model created? first , X-Validation is done as usual, then the final model created from the complete dataset and then outputted? that is what still came not clear to me ....


    ok seems its created a n+1th time on all dataset:

    if you retrieve the model from the outgoing port of the XValidation, then a model is trained on the complete data set. You will notice that in the status bar: After learning / applying the model n times, it will be learned a n+1 time.
    This behavior isn't parameter dependent anymore. It will be produced if the outgoing port is connected (and hence the model will be used later on)



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    Thomas_OttThomas_Ott RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,761 Unicorn

    The model that comes out is a model that is trained on your entire data set.

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