Machine Learning/Data Mining (Classification Technique)
- Applied Model: Decision Tree
- Tool: Python, RapidMiner
This dataset is about consumers and their decisions to terminate a contract (i.e., consumer churn problem).
Data Size: 31891 records
| Col. | Var. Name | Var. Description |
|---|---|---|
| 1 | revenue | Mean monthly revenue in dollars |
| 2 | outcalls | Mean number of outbound voice calls |
| 3 | incalls | Mean number of inbound voice calls |
| 4 | months | Months in Service |
| 5 | eqpdays | Number of days the customer has had his/her current equipment |
| 6 | webcap | Handset is web capable |
| 7 | marryyes | Married (1=Yes; 0=No) |
| 8 | travel | Has traveled to non-US country (1=Yes; 0=No) |
| 9 | pcown | Owns a personal computer (1=Yes; 0=No) |
| 10 | creditcd | Possesses a credit card (1=Yes; 0=No) |
| 11 | retcalls | Number of calls previously made to retention team |
| 12 | churndep | Did the customer churn (1=Yes; 0=No) |
- Data Cleasing
- Modeling
- Model Evaluation
- Model Interpretation