A mini project that utilizes machine learning algorithms to predict customer churn for a telco company, leveraging on classification models such as Random Forest and Naive Bayes.
Data Attributes
7043 observations of 21 variables
1.CustomerID 2.Gender 3.SeniorCitizen 4.Partner 5.Dependents 6.Tenure 7.PhoneService 8.MultipleLines 9.InternetService 10.OnlineSecurity 11.OnlineBackup 12.DeviceProtection 13.TechSupport 14.StreamingTV 15.StreamingMovies 16.Contract 17.PaperlessBilling 18.PaymentMethod 19.MonthlyCharges 20.TotalCharges 21.Churn
Citation: https://www.ibm.com/communities/analytics/watson-analytics-blog/guide-to-sample-datasets/