RegressionTree cannot use "predict" method?

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Young
Young on 30 Mar 2014
Commented: reem aldaihani on 17 Feb 2018
Hello there,
I'm using Matlab R2013a and was able to train a regression tree using RegressionTree.fit(). However, when I used "predict(rtree, test_data)," I got the following error message:
Error using predict (line 85) Systems of classreg.learning.partition.RegressionPartitionedModel class cannot be used with the "predict" command. Convert the system to an identified model first, such as by using the "idss" command.
I believe using "predict" method confused a dynamic model estimation. Can you please tell me what was wrong?
Young

Answers (2)

Young
Young on 9 Jun 2014
Edited: Walter Roberson on 12 Apr 2016
As long as you're not using 'crossval' option, like
rtree = RegressionTree( x, y, 'crossval', 'on' );
The following should work:
[yfit, node] = predict( rtree, test_data );
So, just train a regression tree using "rtree = RegressionTree( train_data, train_label ); and then use it like, [yfit, node] = predict( rtree, test_data )
Young
  1 Comment
reem aldaihani
reem aldaihani on 17 Feb 2018
What if we will use cross-validation? This is part of my code: cvmodel=fitcknn(training_Best,class1, 'Distance',@mindistnew, 'NumNeighbors',1, 'KFold',10); cvclass=predict(cvmodel, testing_Best);
and I received this error:
Systems of classreg.learning.partition.ClassificationPartitionedModel class cannot be used with the "predict" command. Convert the system to an identified model first, such as by using the "idss" command.
Could you please help me to fix this ASAP.

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Sincloe Brans
Sincloe Brans on 9 Jun 2014
Edited: Walter Roberson on 11 Apr 2016
Just do
Yfit = tree([Xnew]);
where tree is your regression or classreg tree and Xnew the new X's to be predicted.

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