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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 Note: Use this link to learn how to divide one dataset into training and test data: https://rpubs.com/ID_Tech/S1 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. Deliverables: 1- Source code (copy the R source code in a .txt file and upload .txt file in D2L) • Note: D2L may not let you upload a file with .R extension 2- The answer to question 4 as a PDF file. Dataset Description: Here is the attribute description for the dataset: Attribute 1: (qualitative) Status of existing checking account • A11: balance = $0A12: balance ≤ $200K • A13: balance > $200K • A14: no checking account Attribute 2: (numerical) Duration of bank membership in month Attribute 3: (qualitative) Credit history • A30: no credits taken/all credits paid back duly • A31: all credits at this bank paid back duly • A32: existing credits paid back duly till now • A33: delay in paying off in the past • A34: critical account/other credits existing (not at this bank) Attribute 4: (qualitative) Purpose of applying for a loan • A40: car (new) • A41: car (used) • A42: furniture/equipment • A43: radio/television • A44: domestic appliances • A45: repairs • A46: education • A47: vacationAttribute 5: (numerical) Credit amount Attribute 6: (qualitative) Savings account/bonds • A61: value < $10K • A62: $10K ≤ value < $50K • A63: $50K ≤ value < $100K • A64: value ≥ $100K • A65: unknown/ no savings account Attribute 7: (qualitative) Present employment since • A71: unemployed • A72: employment period < 1 year • A73: 1 ≤ employment period < 4 years 74: 4 ≤ employment period < 7 years • A75: employment period ≥ 7 years Attribute 8: (numerical) Installment rate in percentage of disposable income Attribute 9: (qualitative) Personal status and sex • A91: male and married/divorced/separated • A92: female and married/divorced/separated • A93: male and single • A94: female and single Attribute 10: (qualitative) Other debtors / guarantors • A101: none • A102: co-applicant • A103: guarantor
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