Ok found out what happened : The Model gets consumed (?) in the first operator of cross validation. However if i save the model first and then read it at the end of the process chain, the decision tree shows fine :
you are right in that a decision tree is shown but its probably not the decision tree you want to look at. The thing is, that the XValidation
is a kind of loop that repeatedly learns a model (by applying the DecisionTree
learner) on a portion of the data and tests its performance on the complementary portion of the data where the actual chosen portion differs from iteration to iteration. Hence, if you save the model inside the XValidation
operator you always save a model which is learned only on a portion of the data. Hence, if you want to learn the complete model in addition to the determination of the learning performance you may simply turn on the parameter learn_complete_model
in the parameters of the XValidation
operator which will then apply the learner once more on the complete set and finally output the resulting model. If you compare the resulting model to the model you wrote out during the cross validation, you will probably observe a difference between them.