I am trying to use the xpred.rpart function to generate an R2/AUC value for cross validation in order to stablish the best cp value but I have had some trouble with it.
In particular, in some cases, when the cp takes "small" values, the values generated by the function (i.e., the predicted values/class) do not make sense.
See the head of the generated matrix below:
As it can be seen, the first five columns contain values that make sense but, from the sixth on, they all contain zeros.
Hi there!
I am trying to use the xpred.rpart function to generate an R2/AUC value for cross validation in order to stablish the best cp value but I have had some trouble with it.
In particular, in some cases, when the cp takes "small" values, the values generated by the function (i.e., the predicted values/class) do not make sense.
See the head of the generated matrix below:
As it can be seen, the first five columns contain values that make sense but, from the sixth on, they all contain zeros.
Is there a way to work this around?
Thank you for your help.