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mobile-app-churn-predictor
jomarie04/mobile-app-churn-predictor
mobile-app-churn-predictor is a machine learning model from jomarie04. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
--- modelname: mobile-app-churn-predictor license: apache-2.0 language: en tags: - tabular - churn-prediction - user-analytics - classification - synthetic-data metrics: - accuracy - rocauc ---
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Updated Jan 27, 2026
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Jan 27, 2026
- Updated
- Jan 27, 2026
- SHA
- 1801c247
Model card
From the Hugging Face model README
model_name: mobile-app-churn-predictor license: apache-2.0 language: en tags:
- tabular
- churn-prediction
- user-analytics
- classification
- synthetic-data metrics:
- accuracy
- roc_auc
Mobile App Churn Predictor
Model Overview
Mobile App Churn Predictor is a machine learning model designed to predict whether a user is likely to churn based on app usage behavior.
The model is trained on synthetic mobile application analytics data and is suitable for demos, tutorials, and experimentation.
Model Details
- Model Name: mobile-app-churn-predictor
- Model Type: Binary Classification
- Framework: scikit-learn
- Input: Tabular CSV data
- Output: Churn probability (Yes / No)
Training Data
Synthetic mobile app usage dataset with the following features:
| Feature | Type | Description |
|---|---|---|
| age | Integer | User age |
| device_os | Categorical | Android / iOS |
| daily_active_minutes | Integer | Avg daily usage |
| sessions_per_day | Integer | App sessions |
| features_used | Integer | Number of features used |
| days_since_install | Integer | Days since app install |
| churn | Binary | Target label |
Intended Use
✅ Churn prediction demos
✅ User behavior modeling
✅ Hugging Face Spaces examples
❌ Production decision-making
Evaluation Results
| Metric | Score |
|---|---|
| Accuracy | 0.88 |
| ROC-AUC | 0.91 |
Limitations
- Synthetic data only
- Simplified user behavior
- Not representative of real-world scale
Ethical Considerations
This model does not use real personal data.
Care should be taken when applying churn models to avoid unfair targeting.
License
This model is released under the Apache License 2.0.
- License
- apache-2.0
- Created
- Jan 27, 2026
- Updated
- Jan 27, 2026