Build a Classification Model Based on the Training Data - IT Assignment Help

Assignment Task

- The dataset (CreditData.csv) classifies customers as “approved” or “not approved” (Yes or No) (i.e., target class).
- The target class is in the 21st column and its name is “Approved”.
- Number of Attributes for Classification: 20 (7 numerical, 13 categorical).
- The task should be developed using R (and in RStudio).

Tasks:
1- Divide data into two datasets
• 80% as training data
• 20% as test data

2- Build a classification model based on the training data to predict if a new customer is approved or not.
• You can use Regression or Decision Tree (or both to learn more!).

3- Test the model on the test data.

4- Explain the model that you build, create the confusion matrix, and report its accuracy, precision, and recall.
• If you use decision tree, draw the tree.
• If you use regression, report the parameters and weight values.

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