Machine learning based system that can predict service cancellation for a business based on its dataset using 5 different machine learning models
Service cancellation is when a customer decides to end thier businesses or unsubscribe from a service with a specific company. This system is oriented to determine the possibility of customers cancelling services. For most businesses, the ability to predict that a particular customer is at a high likelihood of cancelling service could actually result in a better way for handling such problems. Foreseeing business-related actions is the core of this project, and therefore, this system was developed to meet the business related requirements to predict user churn with an average accuracy of 78% with an attractive user-friendly UI.
Dataset Link: Service Cancellation Dataset
Problem stipulated that based on 20 attributes and 7043 record we should make several models that predict whether a user will cancel his service or not we applied 4 models :
Decision Tree (ID3 / CART)Logistic RegressionSVMKNN
Models consumed cleaned data and produced the following accuracies:
| Model | Accuracy |
|---|---|
| Decision Tree(ID3) | 77.69% |
| Decision Tree(CART) | 74.2784% |
| Logistic Regression | 80.7109% |
| SVM | 79.18% |
| KNN | 74.48% |
- Visualising results
