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A cross-comparison of feature selection algorithms on multiple cyber security data-sets
2019
South African Forum for Artificial Intelligence Research
In network intrusion detection, it is essential to detect an attack in realtime and to initiate preventive measures accordingly. This paper aims to evaluate whether SciKit Learn feature selection algorithms improve or worsen the accuracy and processing time of machine learning algorithms when used for network intrusion detection and classification. We develop recommendations of potential machine learning and feature selection algorithms that can be used to obtain a desirable level of accuracy
dblp:conf/fair2/PowellBWA19
fatcat:vzb2s5d4ovcxvco4xazbk7bgm4