Decision tree using Auto model

Arupriya_SenArupriya_Sen Member Posts: 21 Contributor II
edited June 27 in Help
I am doing Fraud Detection Analysis with Decision Tree using Auto Model in RapidMiner version 9.3.0. The dataset and screenshots are attached below. Instead of getting a nice tree, I am getting just a single good leaf. This means that the Auto Model is predicting all the examples of the label attribute to be good.  they are not even showing the decision options. How do I get  a nice proper tree? can anyone help me with this?

Best Answers

  • varunm1varunm1 Posts: 918   Unicorn
    Solution Accepted
    I did check the data and see that your tree is pruned a lot. Please see below screenshots for comparison. To get to the model in automodel, see below screenshot. You need to select model and click open process. Play with pruning parameters and see the results of decision tree model as shown below.



    With Pruning (Default in Automodel): Performance AUC 0.5 



    Without pruning (need to remove manually). Performance AUC 0.59, but the tree is big.



    Hope this helps.

    Varun
    Regards,
    Varun
    Rapidminer Wisdom 2020 (User Track): Call for proposals 

    https://www.varunmandalapu.com/

Answers

  • varunm1varunm1 Moderator, Member Posts: 918   Unicorn
    edited June 21
    Hello @Arupriya_Sen ;

    Due to your status level on the community, we are unable to see the screenshots. @sgenzer can help you post screenshots.

    Coming to the auto model question, did you check the process to see if the decision tree parameter pruning is selected. If so, it might be the reason your tree is pruned a lot and some time all. To open the process you need to select a model under a decision tree in the left bar and then click open process on the top.

    Also please do not post duplicate questions on the community, they might get tagged as duplicate. You can modify your question using an edit option (Click on wheel icon and edit).

    https://community.rapidminer.com/discussion/55732/decision-tree-using-auto-model#latest

    Thanks
    Varun
    Regards,
    Varun
    Rapidminer Wisdom 2020 (User Track): Call for proposals 

    https://www.varunmandalapu.com/
    Arupriya_Sen
  • Arupriya_SenArupriya_Sen Member Posts: 21 Contributor II
    Thank you so much for the solution. It really helped. Can you tell me how to reduce the maximal gain parameter to 15 from 25? when I'm changing it and running the process, it is automatically set back to 25.
  • Arupriya_SenArupriya_Sen Member Posts: 21 Contributor II
    Thank you so much once again.  :) If I have to closely look at the Confusion Matrix or the performance of the tree, the Auto Model is not even taking into  consideration all the 999 examples. Isn't that wrong? The True bad are 23 and 65 and the true good are 17 and 180. 
  • Arupriya_SenArupriya_Sen Member Posts: 21 Contributor II
    Can you also help me with the Predictions of the decision tree under the Prediction Tab? there are various colours used which I can't interpret.
  • Arupriya_SenArupriya_Sen Member Posts: 21 Contributor II
    Can you help me in removing this error in the screenshot attached below? I have circled the error with red.
  • Arupriya_SenArupriya_Sen Member Posts: 21 Contributor II
    Can you help me remove the errors as well? The errors are circled in red in the screenshots attached below.
     
  • Arupriya_SenArupriya_Sen Member Posts: 21 Contributor II
    I am facing the following errors:


    The 4th and 1st ones are for the same operators. The rest of the two are for different operators. 
  • Arupriya_SenArupriya_Sen Member Posts: 21 Contributor II
    Hello @varunm1, could you help me here? Thanks in advance.
  • Arupriya_SenArupriya_Sen Member Posts: 21 Contributor II
    @sgenzer any suggestions here? It's extremely urgent. 
  • sgenzersgenzer 12Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,609  Community Manager
    @Arupriya_Sen hmm sorry I am completely lost on this thread. Can you please explain what's going on at this point?
  • Arupriya_SenArupriya_Sen Member Posts: 21 Contributor II
    @sgenzer I am doing Fraud Detection Analysis with Decision Tree using Auto Model in RapidMiner version 9.3.0. The dataset and xml process are attached below. Even though I am getting results, many of the operators are showing errors and I can't understand how to remove them. Could you please help me with the same? Urgent help needed. Thanks in advance. 

  • sgenzersgenzer 12Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,609  Community Manager
    hi @Arupriya_Sen very sorry for the delay - I was on vacation from July 3 until now. Do you still need help with this?
  • Telcontar120Telcontar120 Moderator, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,270   Unicorn
    Many of these errors are not fatal errors but simply warnings.
    For example  about the path locations of your datasets---if they are not set as relative paths, then if you move or share the process, the links will not work properly.
    Or the error about the attribute name may be because you don't have any such attribute in the dataset, or the metadata for that attribute has not yet propagated.
    In general, if your process runs and completes and gives you the expected output, then these types of warning errors can be disregarded.  Of course if your process doesn't complete, then you have a serious error that needs resolution.


    Brian T.
    Lindon Ventures 
    Data Science Consulting from Certified RapidMiner Experts
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