decision tree
Description
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Dr. Jim
Homework 8 ecision Trees
Due date: November 17, 2022 at 6:15 pm
In this homework, you will apply a decision tree model to a data set of your choice. Perform the
following tasks for this homework:
1. Find a different data set of your choice from a valid source. Break up your data set into a
training set and a scoring set and label them as such.
2. In the Research Question section, write a legitimate question that you want answered
from your data.
3. Determine which attribute should be the !bel&or your model. Remove this attribute
from your scoring data set since this is the attribute that we will predict.
4. Import both training and scoring sets into RapidMiner. Apply the necessary åt Role¯perator(s). Run the model to check if the special attribute(s) have their roles set
correctly. Take screenshots of both the training and scoring set.
5. Generate a decision tree model and apply the model. Take a screenshot of the final
process stream.
6. Run the model and take screenshots of both the decision tree and the results of the
predictions made on the scoring data set. Play around with the parameters in the
Decision Tree operator (especially tree algorithm criteria, minimal gain, and minimal leaf
size) and rerun the model.
7. Evaluate and interpret your results. Answer your research question, and note any
interesting or unexpected results. Also, note any differences in your treeàstructure and
analyze and report your results when changing the tree algorithm criteria, minimal gain,
and minimal leaf size parameters.
Submission Instructions:
Please type up your homework using the homework template posted on Blackboard under
Assignments. You should include at least five screenshots: (1) training data set with special
attribute(s), (2) scoring data set, (3) final process stream, (4) decision tree model, and (5) results of
predictions made on the scoring data set. Remember to interpret your results. Only a softcopy
submission is needed through the assignment link posted on Blackboard.
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