"RM6.5 Decision Tree help"

tanthiamhuattanthiamhuat Member Posts: 4 Contributor I
edited June 2019 in Help
can anyone guide me how to use the Decision Tree in RM 6.5, such that I am able to get the Pruned Classification Tree from http://www.edureka.co/blog/implementation-of-decision-tree/

the dataset is from http://www.ats.ucla.edu/stat/data/binary.csv


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    MariusHelfMariusHelf RapidMiner Certified Expert, Member Posts: 1,869 Unicorn

    if you're new to RapidMiner, have a look at http://j.mp/20LVJQ1 to learn how to train a decision tree in RapidMiner and how to validate it.
    The Decision Tree operator in RapidMiner has some pruning options -- the operator help describes them all.

    You can even automatically optimize them -- have a look at the Optimize Parameters (Grid) operator for that.

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    Anand1629Anand1629 Member Posts: 1 Newbie

    Decision trees are a popular machine learning algorithm used in data science to classify data. In RapidMiner 6.5, you can use the Decision Tree operator to create a decision tree model. Here are the steps:

    1. Load your dataset into RapidMiner 6.5.
    2. Drag the Decision Tree operator from the Operator Toolbox onto the Process panel.
    3. Connect the input port of the Decision Tree operator to your dataset.
    4. Open the operator parameters dialog by double-clicking on the operator.
    5. Configure the parameters for the Decision Tree operator, such as the target attribute, number of folds for cross-validation, and pruning method.
    6. Run the operator to generate the decision tree model.
    7. Evaluate the performance of the model using the validation operator or other evaluation methods.

    If you're interested in learning more about data science and machine learning, there are many  online courses 

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