In this project we will explore Logistic Regression type of model and learn more about the subject on these following features:
Customer ID: The Id of the customer.
Gender: Is the customer male or female.
SeniorCitizen: Whether the customer is a senior citizen or not.
Partner: Whether the customer has a partner or not.
Dependents: Whether the customer has dependents or not.
Tenure: Number of months the customer has stayed with the company.
Phone Service: Whether the customer has a phone service or not.
MultipleLines: Whether the customer has multiple lines or not.
InternetService: Customers internet service provider.
OnlineSecurity: Whether the customer has online security or not.
OnlineBackup: Whether the customer has online backup or not.
DeviceProtection: Whether the customer has device protection or not.
TechSupport: Whether the customer has tech support or not.
StreamingTV: Whether the has a streaming TV or not.
StreamingMovies: Whether the customer has streaming movies or not.
Contract: The contract term of the customer.
PaperlessBilling: Whether the customer has paperless billing or not.
PaymentMethod: The customer’s payment method.
MonthlyCharges: The amount charged to the customer monthly.
TotalCharges: The total amount charged to the customer.
Churn: Whether the customer churned or not (Target Column).
After testing the model we founds this Accuracy:
The best Score is 80.57%
