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 7 months ago)

Stargazers 348 (3 this week)

Watchers 10 (0 this week)

Forks 91

License mit

Ranking

RepositoryStats indexes 523,840 repositories, of these Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning is ranked #110,955 (79th percentile) for total stargazers, and #198,405 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #2,319/14,471.

Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning is also tagged with popular topics, for these it's ranked: machine-learning (#2,345/7264), autonomous-vehicles (#41/166), cyber-security (#31/129), hyperparameter-optimization (#46/113), network-security (#42/101)

Other Information

Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning has Github issues enabled, there is 1 open issue and 3 closed issues.

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: 2024-05-31 @ 06:05pm, id: 370748417 / R_kgDOFhksAQ