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Tania
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predict does not work with a crossvalidated tree?

Asked by Tania
on 1 Aug 2014
Latest activity Commented on by Tania
on 1 Aug 2014
Hey, I am trying to do the following: rtree = RegressionTree.fit(X,Y,'crossval','on'); pred = predict(rtree,X)
But unfortunately I get a error message.
Does anyone know what I can use instead of pred?
Thank you!

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1 Answer

Answer by Shashank Prasanna on 1 Aug 2014
 Accepted Answer

When you use the 'crossval' 'on' flag you get a partitioned model as an output. You can predict from this model using
kfoldpredict

  1 Comment

Great, it worked!:) Do you know maybe also the other to this question: What is the difference between 'control depth' and 'pruning' in the 'improving classification and regression trees' documentation:
I dont understand why they do both...?!?Both are trying to find the optimal depth through cross validation...
Thanks!

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