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GitHub / 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..)

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Western-OC2-Lab%2FIntrusion-Detection-System-Using-Machine-Learning

Stars: 259
Forks: 62
Open Issues: 0

License: mit
Language: Jupyter Notebook
Repo Size: 17.7 MB
Dependencies: 0

Created: about 3 years ago
Updated: 7 months ago
Last pushed: 8 months ago
Last synced: 7 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

Files

Readme

No dependencies found