  Militarised conflict is one of the risks that have a significant impact on
society. Militarised Interstate Dispute (MID) is defined as an outcome of
interstate interactions, which result on either peace or conflict. Effective
prediction of the possibility of conflict between states is an important
decision support tool for policy makers. In a previous research, neural
networks (NNs) have been implemented to predict the MID. Support Vector
Machines (SVMs) have proven to be very good prediction techniques and are
introduced for the prediction of MIDs in this study and compared to neural
networks. The results show that SVMs predict MID better than NNs while NNs give
more consistent and easy to interpret sensitivity analysis than SVMs.
