Many machine learning algorithms have been used to classify network traffic flows with good performance, but without information about the reliability in classifications. In this paper, we present a recently developed algorithmic framework, namely the Venn Probability Machine, for making reliable decisions under uncertainty. Experiments on publicly available real traffic datasets show the algorithmic framework works well. Comparison is also made to the published results.
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