Expert answer:Intro to Data Analytics/Business Data Mining

Expert answer:n this homework, you will apply a decision tree model to a data set of your choice. Perform the following tasks for this homework: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.In the Research Question section, write a legitimate question that you want answered from your data.Determine which attribute should be the ‘label’ for your model. Remove this attribute from your scoring data set since this is the attribute that we will predict.Import both training and scoring sets into RapidMiner. Apply the necessary “Set Role” operator(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.Generate a decision tree model and apply the model. Take a screenshot of the final process stream.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.Evaluate and interpret your results. Answer your research question, and note any interesting or unexpected results. Also, note any differences in your tree’s structure 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.NateUse the RapidMiner. progra, also i need at least five screenshots
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Intro to Data Analytics/Business Data Mining
Homework 8 – Decision Trees
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 ‘label’ for 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 “Set Role”
operator(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 tree’s structure 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.
ITMG 516, FALL 2017
NAME:
HOMEWORK #:
RESEARCH QUESTION:
DATA SET SOURCE:
NUMBER OF COLUMNS:
NUMBER OF ROWS:
SCREENSHOTS:
INTERPRETATION OF RESULTS:
DATE:
…
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