A machine learning project utilizing the decision tree algorithm to predict the credit score of customers.
This project utilizes machine learning techniques to predict the credit score of customers based on various predictors. The decision tree algorithm is employed for the predictive modeling.
The dataset used for this project can be found here. It includes features such as:
- Customer_ID
- Month
- Name
- Age
- SSN
- Occupation
- Annual_Income
- Monthly_Inhand_Salary
- Num_Bank_Accounts
- Num_Credit_Card
- Interest_Rate
- Num_of_Loan
- Type_of_Loan
- Delay_from_due_date
- Num_of_Delayed_Payment
- Changed_Credit_Limit
- Num_Credit_Inquiries
- Credit_Mix
- Outstanding_Debt
- Credit_Utilization_Ratio
- Credit_History_Age
- Payment_of_Min_Amount
- Total_EMI_per_month
- Amount_invested_monthly
- Payment_Behaviour
- Monthly_Balance
To run the code:
- Clone this repository.
- Install the necessary dependencies.
- Execute the main script.
- Python
- scikit-learn
- pandas
- numpy
- plotly