Mitigating label noise in network intrusion detection via graph-based sample selection and purification.

It also shows a strong trend over INCV and MCRe, though the difference is marginally significant (p \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\approx$$\end{document} 0.063).On the DoHBrw dataset, our approach achieves statistical significance against all baselines (p = 0.0312 < 0.05 for each comparison).

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