GitHub / MohEsmail143 / network-anomaly-detection

An attempt at the network anomaly detection task using manually implemented k-means, spectral clustering and DBSCAN algorithms, with manually implemented evaluation metrics (precision, recall, f1-score and conditional entropy) used to evaluate these algorithms.

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Topics: conditional-entropy, dbscan, dbscan-clustering, f1-score, jupyter-notebook, k-means, k-means-clustering, machine-learning, network-anomaly, network-anomaly-detection, normalized-cuts, precision, python, recall, spectral-clustering, spectral-clustering-algorithm, unsupervised-learning, unsupervised-machine-learning

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