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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..)

License: MIT License

Jupyter Notebook 100.00%
machine-learning random-forest decision-tree xgboost bayesian-optimization hyperparameter-optimization hpo kmeans python-examples intrusion-detection

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intrusion-detection-system-using-machine-learning's Issues

I have a question about code

In function Anomaly_IDS, there has one code acc = metrics.accuracy_score(y2, result2), but i get a error like "Unresolved reference 'y2'", can i get your help

Problems with oversampling

After setting up the oversampling parameters, when oversampling the training set of X and Y, the following error occurs please tell me how to solve it。
ValueError: Unknown label type: unknown. Maybe you are trying to fit a classifier, which expects discrete classes on a regression target with continuous values.

Lack of memory

How did you exactly run the Tree-base jupyter notebook on the original CIDIDS2017 dataset, it's insane!!! 16 GB of memory is far from being enough to support the whole exps.

Regarding CICIDS2017 Dataset

I have the CICIDS2017 dataset file but after concatinating all Days .CSVs, the merged file is getting too long and it is not getting processed. Coould you please provide the CICIDS2017 file (as only sample file is given in data folder) to execute the code successively.

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