Identification of subgroups of terror attacks with shared characteristics for the purpose of preventing mass-casualty attacks: a data-mining approach

Table 1 Performance measures for different interpretable classification algorithms

Interpretable classification algorithm	Performance measure for “positive” events	Overall performance measures
Interpretable classification algorithm	\(AUC_{High}\)	\(AUC\)	\(KE\)
C4.5	0.832	0.841	0.468
Naïve Bayes	0.797	0.781	0.343
Bayesian Network	0.818	0.800	0.375
PART	0.752	0.765	0.435

ISSN: 2193-7680