Decision Tree Produces All Same Predictions and Probabilities

scooter7scooter7 Member Posts: 8 Contributor II
edited November 2018 in Help

I have created a decision tree model that is highly accurate at predicting a nominal binary (yes/no) outcome for both the yeses and nos.

When I write the model and then read it into a new scoring process, every prediction is exactly the same in terms of predicted outcome and probabilities of yes or no. I have experienced the same issue with these data when using various types of tree algorithms. Using naive bayes and some other models does not produce the same problem.

Could I send you the xml as well as the training and scoring files to see if you can help me figure out what is going on?



  • MartinLiebigMartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,507 RM Data Scientist

    have you checked if your tree is a real tree and not just a stump?

    - Sr. Director Data Solutions, Altair RapidMiner -
    Dortmund, Germany
  • scooter7scooter7 Member Posts: 8 Contributor II

    I have checked and confirmed that it is a real tree. However, I believe that I solved the problem, which turned out to be a data-related issue and unrelated to the software.

    Thanks for your help!
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