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Figure 10. Performance metrics (One vs. Rest) for reconstruction of all features values when feature: ‘flag’ is missing. Figure 11. Performance metrics (One vs. Rest) for reconstruction of all features values when feature: ‘service’ is missing. Figures 9 and 10 present results for the recovery metrics for all values of the protocol and flag features (with three and 11 values, respectively) and Figure 11 presents results for the 10 most frequent values of the service feature, which has 70 values in total. In Figure 9, when recovering the protocol feature we can achieve an F1 score of not less than 0.96 for any value of the feature, regardless of its frequency. While recovering the flag feature (Figure 10), we obtain an accuracy always greater than 0.97 and an F1 score greater than 0.9 for the most frequent values. Doctoral Thesis: Novel applications of Machine Learning to NTAP - 142PDF Image | Novel applications of Machine Learning to Network Traffic Analysis
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