A complete pipeline for network intrusion detection comparing label encoding and one‑hot encoding, with SMOTE resampling, feature selection, and ensemble modeling using scikit‑learn and XGBoost, also this was phase one of our University's "CSAI 253- Machine Learning" course.
machine-learning machine-learning-algorithms cybersecurity xgboost feature-engineering smote network-intrusion-detection imbalanced-learning cybersecurity-training sckit-learn one-hot-encoding ensamble-methods zewailcity tree-based-model csai-253
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Updated
Jun 23, 2025 - Jupyter Notebook