https://github.com/mohamed-samy26/service-cancellation-predictor
Machine learning based system that can predict service cancellation for a business based on its dataset using 5 models
https://github.com/mohamed-samy26/service-cancellation-predictor
cart-algorithm data-cleaning decision-trees id3 jupyter-notebook knn logistic-regression machine-learning python svm tkinter
Last synced: about 1 month ago
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Machine learning based system that can predict service cancellation for a business based on its dataset using 5 models
- Host: GitHub
- URL: https://github.com/mohamed-samy26/service-cancellation-predictor
- Owner: Mohamed-Samy26
- Created: 2022-04-28T22:46:07.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-06-25T04:35:56.000Z (over 3 years ago)
- Last Synced: 2025-03-01T20:32:06.404Z (7 months ago)
- Topics: cart-algorithm, data-cleaning, decision-trees, id3, jupyter-notebook, knn, logistic-regression, machine-learning, python, svm, tkinter
- Language: Jupyter Notebook
- Homepage:
- Size: 3.5 MB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Service Cancellation Predictor
Machine learning based system that can predict service cancellation for a business based on its dataset using 5 different machine learning models
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## About Project
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](https://drive.google.com/file/d/1PrE7kY9h8yTawg0Ul0Ij5RFjiSO0hdYk/view)
## Problem and Algorithms
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 Regression `
* `SVM `
* `KNN`
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% |## GUI
### Splash Screen
### Main Screen
#### Empty with no data



#### All data filled


#### When customer cancels the service

#### When customer keeps the service

#### Training model on input data

#### Testing models accuracy

* Visualising results

## Contributors
- [Mohamed-Samy26](https://github.com/Mohamed-Samy26)
- [RedBiscuits](https://github.com/RedBiscuits)
- [KareemHussen](https://github.com/KareemHussen)
- [NourAyman10](https://github.com/NourAyman10)
- [HaneenIbrahim2](https://github.com/HaneenIbrahim2)
- [OmarSherif2](https://github.com/OmarSherif2)
- [Abdelrhman-Sayed70](https://github.com/Abdelrhman-Sayed70)