Question 1:Partition the data to create a training data set (70%) and test data set (30%).Solution: Below are screenshots showing the data setup (refer 1.0 Data Setup) and partitioning (refer 1.1 Partitioning Criteria)1.0 Data Setup1.1 Partitioning Criteria
Question 2: Build a single classification tree with the training data and Default as the target. Include the "Default Tree Model" output when submitting the answer.
2.2 Default Tree (2)1.Which variable(s) were used in the tree model?
2.1.1 Fields used2.How would you use the model to predict whether or not the customer will default?
3.What is the accuracy of the model when using the training and test data? Include the "Misclassification Table" outputs when submitting the answer.2.3.1 Accuracy of the model & Misclassification Table4.Consider the following individual: Limit_Balance=5000, Sex=Male, Education=High School, Marital_Status=Married, Age=30, Pay_Status1=On Time, Pay_Status2=On Time, Pay_Status3=2 Mths Late, Pay_Amt_Prev1=0, Pay_Amt_Prev2=0, Pay_Amt_Prev3=0,