https://github.com/cyprianfusi/validating_ml_models
This repo in due time shall contain notebooks with exercises demonstrating various methods of validating ML models
https://github.com/cyprianfusi/validating_ml_models
Last synced: 10 months ago
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This repo in due time shall contain notebooks with exercises demonstrating various methods of validating ML models
- Host: GitHub
- URL: https://github.com/cyprianfusi/validating_ml_models
- Owner: CyprianFusi
- Created: 2022-05-14T09:44:00.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-05-14T09:53:40.000Z (over 3 years ago)
- Last Synced: 2025-01-26T11:28:35.146Z (12 months ago)
- Language: Jupyter Notebook
- Size: 114 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# validating_ML_models
This repo in due time shall contain notebooks with exercises demonstrating various methods of validating ML models
Validating Logistic Regression model: Decile Analysis
The main focus of this exercise is to use **decile analysis** to evalute the performance of a **logistic regression** model.
This will include **decile chart** and **lift chart** and their visualizations.
Binary classifications also use the **Area Under Curve (AUC)** and the **Kolmogorov–Smirnov (KS) distance** to evaluate the model.
We shall also calculate and interpret these statistics.