NSL-KDD-Network-Intrusion-Detection and Network-Intrusion-Detection-Using-Machine-Learning-Techniques
These are complementary implementations that address the same problem domain—they both perform network intrusion detection using machine learning—but one (A) demonstrates multiple classification algorithms while the other (B) focuses specifically on the NSL-KDD benchmark dataset, making them useful together for comparative evaluation and validation across different datasets and models.
About NSL-KDD-Network-Intrusion-Detection
Mamcose/NSL-KDD-Network-Intrusion-Detection
Machine Learning Algorithms on NSL-KDD dataset
About Network-Intrusion-Detection-Using-Machine-Learning-Techniques
dimtics/Network-Intrusion-Detection-Using-Machine-Learning-Techniques
Network intrusions classification using algorithms such as Support Vector Machine (SVM), Decision Tree, Naive Baye, K-Nearest Neighbor (KNN), Logistic Regression and Random Forest.
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