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How to use Regression Tree(CART - Variance reduction)

krim3405krim3405 Member Posts: 2 Contributor I
edited October 15 in Help
Hello
I am looking for Decision Tree operator for Regression (CART - Variance reduction)

But I can't find it

anyone know where can i find it ?
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Best Answer

  • krim3405krim3405 Posts: 2 Contributor I
    Solution Accepted
    What is the Base algorithm of the Decision Tree in the Rapid Miner?

Answers

  • varunm1varunm1 Moderator, Member Posts: 907   Unicorn
    Hello @krim3405

    Did you try the decision tree with "least squares" as a criterion? This is used for regression rapidminer.
    Regards,
    Varun
    Rapidminer Wisdom 2020 (User Track): Call for proposals 

    https://www.varunmandalapu.com/
  • mbsmbs Member, KB Contributor Posts: 221  Guru
    @krim3405


    Hi

    Synopsis

    This Operator generates a decision tree model, which can be used for classification and regression.

    Description

    A decision tree is a tree like collection of nodes intended to create a decision on values affiliation to a class or an estimate of a numerical target value. Each node represents a splitting rule for one specific Attribute. For classification this rule separates values belonging to different classes, for regression it separates them in order to reduce the error in an optimal way for the selected parameter criterion.

    The building of new nodes is repeated until the stopping criteria are met. A prediction for the class label Attribute is determined depending on the majority of Examples which reached this leaf during generation, while an estimation for a numerical value is obtained by averaging the values in a leaf.

    This Operator can process ExampleSets containing both nominal and numerical Attributes. The label Attribute must be nominal for classification and numerical for regression.

    After generation, the decision tree model can be applied to new Examples using the Apply Model Operator. Each Example follows the branches of the tree in accordance to the splitting rule until a leaf is reached.

    To configure the decision tree, please read the documentation on parameters as explained below.


    look at this link please:

    https://docs.rapidminer.com/latest/studio/operators/modeling/predictive/trees/parallel_decision_tree.html


    regards 

    mbs


  • varunm1varunm1 Moderator, Member Posts: 907   Unicorn
    Hello @krim3405

    There is no single base model for decision tree operator in rapid miner, it switches based on your selection of criterion. So my understanding for least squares is a modified version of CART.

    @IngoRM or @gmeier any suggestions here?
    Regards,
    Varun
    Rapidminer Wisdom 2020 (User Track): Call for proposals 

    https://www.varunmandalapu.com/
  • sgenzersgenzer 12Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,581  Community Manager
    edited October 15
    hi @krim3405 yes @varunm1 is correct of course. The best way to answer your question is simply to share the code with you. All of RapidMiner's learner operators are 100% open source on GitHub. :smile:

    https://github.com/rapidminer/rapidminer-studio/tree/3a2da3e40bbadaf5515e04093867798c27d0654d/src/main/java/com/rapidminer/operator/learner/tree

    Scott
    ----------------------
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    varunm1
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