Table 4.

Overall identification accuracy for several algorithms.

Experiment	Identification Algorithm	Number of Events	Applied Features	Identification Accuracy
A	kNN	128	34, 36–133	85.69%
B	Random Forest	128	34, 36–133	85.69%
C	Rule Induction	84	1–69	65.47%
D	Random Forest	84	1–69	87.69%
E	Decision Tree	175	34, 36–39, 46, 49, 55, 56, 60, 70, 71, 74, 77, 79, 80, 87, 88, 92, 94	92.57%
F	Ensemble (DT, RI, RF)	128	1–69	92.96%