"RM6.5 Decision Tree help"

tanthiamhuat

can anyone guide me how to use the Decision Tree in RM 6.5, such that I am able to get thePruned Classification Treefromhttp://www.edureka.co/blog/implementation-of-decision-tree/

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

MariusHelf

Hi,

if you're new to RapidMiner, have a look athttp://j.mp/20LVJQ1to learn how to train a decision tree in RapidMiner and how to validate it.
在RapidMiner有决策树操作符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.

~Marius

Anand1629

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