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..)

Date Created 2021-05-25 (3 years ago)

Commits 50 (last one about a year ago)

Stargazers 467 (2 this week)

Watchers 12 (0 this week)

Forks 122

License mit

Ranking

RepositoryStats indexes 622,366 repositories, of these Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning is ranked #98,957 (84th percentile) for total stargazers, and #180,683 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #2,145/18,620.

Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning is also tagged with popular topics, for these it's ranked: machine-learning (#2,156/8311), autonomous-vehicles (#43/190), cyber-security (#32/163), network-security (#44/127), hyperparameter-optimization (#42/126)

All Topics

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

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Recent Commit History

29 commits on the default branch (main) since jan '22

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Languages

The only known language in this repository is Jupyter Notebook

updated: 2025-03-03 @ 12:18pm, id: 370748417 / R_kgDOFhksAQ