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---
language: en
license: apache-2.0
tags:
- xgboost
- machine-learning
- classification
- cybersecurity
- phishing-detection
datasets:
- custom
metrics:
- accuracy
- precision
- recall
- f1
---
# XGBoost Phishing Detection Models
## Model Description
XGBoost models trained for phishing detection using URL and HTML content features.
This model is trained using XGBoost for binary classification tasks.
## Model Architecture
- **Model Type**: XGBoost Classifier
- **Framework**: XGBoost
- **Task**: Binary Classification
## Usage
```python
import joblib
from huggingface_hub import hf_hub_download
# Download the model
model_path = hf_hub_download(repo_id="th1enq/xgboost_checkpoint", filename="xgboost phishing detection models.joblib")
# Load the model
model = joblib.load(model_path)
# Make predictions
predictions = model.predict(X_test)
```
## Training
The model was trained using the XGBoost library with the following approach:
- Feature extraction from URLs/HTML content
- Binary classification (legitimate vs phishing)
- Cross-validation for model evaluation
## Files
- `xgboost phishing detection models.joblib`: The trained XGBoost model
- `features.py`: Feature extraction functions
- `URLFeatureExtraction.py`: URL-specific feature extraction
## License
This model is released under the Apache 2.0 License.
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