Clustering traffic flows with histogram, ACF, PSD or naive representations improves traffic matrix prediction over global models on Abilene and GÉANT data, with most gains at moderate cluster counts and similar accuracy across representations.
Shapley values of reconstruction errors of pca for explaining anomaly detection
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A single fixed term in the Shapley value yields the same anomaly localization error probability as the full calculation for independent sensor observations, supported by a proof.
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On the Role of Time Series Clustering in Traffic Matrix Prediction
Clustering traffic flows with histogram, ACF, PSD or naive representations improves traffic matrix prediction over global models on Abilene and GÉANT data, with most gains at moderate cluster counts and similar accuracy across representations.
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On Using the Shapley Value for Anomaly Localization: A Statistical Investigation
A single fixed term in the Shapley value yields the same anomaly localization error probability as the full calculation for independent sensor observations, supported by a proof.