Network intrusion is a subject of great concern to a variety of stakeholders. Decision fusion
(ensemble) models that combine several base learners have been widely used to enhance
detection rate of unauthorised network intrusion. However, the design of such an optimal
decision fusion classifier is a challenging and open problem. The Matthews Correlation
Coefficient (MCC) is an effective measure for detecting associations between variables in
many fields; however, very few studies have applied it in selecting weak learners to the best …