th1enq/xgboost_checkpoint

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

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.