Skip to content

amitabhanand21/Bank-Churn-Prediction

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 
 
 

Repository files navigation

Bank Churn Prediction

Aim of this code is to find the most accurate and precise model to predict, which clients (test data) will stay and which are hesitant and might plan to leave the company.

Dataset has following attributes:

Rownumber: Unique ID for every row
CustomerID: Unique ID for every client
Surname: Client's surname
CreditScore: Client's credit score
Geography: Country of client's origin
Gender: Client's gender
Age: Client's age
Tenure: Number of years for which the client has been with the bank
Balance: Client's balance on account
NumOfProducts: Number of client's products
HasCrCard: Flag whether client has credit card or not
IsActiveMember: Flag whether client is active member of bank or not
EstimatedSalary: Client's annual estimated salary in euros
Exited: Target variable, flag, whether client left the bank or not

Used random over sampler since target variable was highly non-homogeneous.

About

Bank customers churn prediction

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors