GitHub / jeremy191 / clustering-based-anomaly-detection
This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets
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PURL: pkg:github/jeremy191/clustering-based-anomaly-detection
Stars: 57
Forks: 13
Open issues: 0
License: mit
Language: Jupyter Notebook
Size: 13.4 MB
Dependencies parsed at: Pending
Created at: over 6 years ago
Updated at: 5 months ago
Pushed at: almost 6 years ago
Last synced at: 4 months ago
Topics: anaconda, anomaly-detection, clustering, clustering-algorithms, dataset, dbscan-algorithm, f1-score, ids2017, isolation-forest, kmeans-clustering, lof, min-max-scaler, missing-values, normalized-mutual-info, nsl-kdd, onehot-encoder, score-metrics, simple-imputer