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| # Phishing Detection Model Performance | |
| ## Overview | |
| This project develops a machine learning model for detecting phishing URLs using URLScan.io API data. | |
| ## Model Performance Over Time | |
| ### Performance Metrics | |
| Track how the model's performance evolves over time to identify improvements or degradation. | |
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| ### Confusion Matrix | |
| Latest model confusion matrix showing prediction accuracy across classes. | |
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| ### Feature Drift Detection | |
| Monitor feature drift to detect changes in data distribution that may affect model performance. | |
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| ## Dataset Information | |
| - **Source**: URLScan.io API + Phishing URL datasets | |
| - **Training samples**: TBD | |
| - **Test samples**: TBD | |
| - **Features**: TBD | |
| ## Model Architecture | |
| Details about the model architecture, feature engineering, and training process will be documented here. | |
| ## Latest Updates | |
| Check back for updates on model performance and improvements. | |
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| _Last updated: {{ site.time | date: "%Y-%m-%d" }}_ | |