This is a synthetic dataset for the Playground Series S4 E1 Binary Classification with a Bank Churn Dataset.

Description:

- Surname : Label Encoded Surnames

- Surname_tfidf_0-4 : Features made by applying TFIDF Vectorizer to the Surnames

- Credit Score : A numerical value representing the customer's credit score

- Geography: The country where the customer resides (France, Spain or Germany)

- Gender: The customer's gender (Male or Female)

- Age: The customer's age.

- Tenure: The number of years the customer has been with the bank

- Balance: The customer's account balance

- NumOfProducts: The number of bank products the customer uses (e.g., savings account, credit card)

- HasCrCard: Whether the customer has a credit card (1 = yes, 0 = no)

- IsActiveMember: Whether the customer is an active member (1 = yes, 0 = no)

- EstimatedSalary: The estimated salary of the customer

- Exited: Whether the customer has churned (1 = yes, 0 = no)

- Germany, France, Spain: One Hot Encoded Geography feature

- Male, Female: One Hot Encoded Gender feature

- Mem__no__Products: NumOfProducts * IsActiveMember

- Cred_Bal_Sal: (Credit Score * Balance) / EstimatedSalary

- Bal_sal: Balance / EstimatedSalary

- Tenure_Age: Tenure / Age

- Age_Tenure_product: Age * Tenure