https://github.com/Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning

Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
https://github.com/Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning

autonomous-vehicles bayesian-optimization catboost cicids2017 cyber-security decision-tree ensemble-learning hpo hyperparameter-optimization intrusion-detection intrusion-detection-system kmeans lightgbm machine-learning network-security python-examples random-forest stacking xgboost

Last synced: 5 months ago
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Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)

• Host: GitHub
• URL: https://github.com/Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning
• Owner: Western-OC2-Lab
• License: mit
• Created: 2021-05-25T15:50:41.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2023-10-13T11:41:39.000Z (over 1 year ago)
• Last Synced: 2024-08-09T13:21:33.449Z (9 months ago)
• Topics: autonomous-vehicles, bayesian-optimization, catboost, cicids2017, cyber-security, decision-tree, ensemble-learning, hpo, hyperparameter-optimization, intrusion-detection, intrusion-detection-system, kmeans, lightgbm, machine-learning, network-security, python-examples, random-forest, stacking, xgboost
• Language: Jupyter Notebook
• Homepage:
• Size: 17.7 MB
• Stars: 381
• Watchers: 10
• Forks: 98
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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