Analyzing the customer’s information from the dataset, including credit history, income, employment status, and other relevant features, to predict whether an applicant is likely to be a responsible cardholder.
To predict the approval of the customer’s credit card application.
- SAS File:
- Executive Summary:
- Presentation:
- Data Sets:
Ind_ID: Client ID
Gender: Gender information
Car_owner: Having car or not
Propert_owner: Having property or not
Children: Count of children
Annual_income: Annual income
Type_Income: Income type
Education: Education level
Marital_status: Marital_status
Housing_type: Living style
Birthday_count: Use backward count from current day (0), -1 means yesterday.
Employed_days: Start date of employment. Use backward count from current day (0). Positive value means, individual is currently unemployed.
Mobile_phone: Any mobile phone
Work_phone: Any work phone
Phone: Any phone number
EMAIL_ID: Any email ID Type_Occupation: Occupation Family_Members: Family size Another data set (Credit_card_label.csv) contains two key pieces of information