The Orange Telecom's Churn Dataset, which consists of cleaned customer activity data (features), along with a churn label specifying whether a customer canceled the subscription, will be used to develop our predictive model. The churn-80 and churn-20 datasets can be downloaded from the following links, respectively:
- https://bml-data.s3.amazonaws.com/churn-bigml-80.csv
- https://bml-data.s3.amazonaws.com/churn-bigml-20.csv
However, as more data is often desirable for developing ML models, let's use the larger set (that is, churn-80) for training and cross-validation purposes, and the smaller set (that is, churn-20) for final testing and model performance evaluation.
Note that the latter set is only used to evaluate the model (that is for demonstration purposes). For a production ready environment, telecommunication companies can use their own dataset with necessary preprocessing and feature engineering. The dataset has the following schema:
- State: String
- Account length: Integer
- Area code: Integer
- International plan: String
- Voicemail plan: String
- Number email messages: Integer
- Total day minutes: Double
- Total day calls: Integer
- Total day charge: Double
- Total eve minutes: Double
- Total eve calls: Integer
- Total eve charge: Double
- Total night minutes: Double
- Total night calls: Integer
- Total night charge: Double
- Total intl minutes: Double
- Total intl calls: Integer
- Total intl charge: Double
- Customer service calls: Integer