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Table 4 Prediction accuracy of the selected model with respect to each dataset

From: A deep learning framework for predicting cyber attacks rates

Dataset MSE MAD PMAD MAPE
ARIMA
I 40,054,811 5,038.95 0.1352803 0.1378065
II 100,487,103 6,763.351 0.2618205 0.314159
III 47,486,461 3,478.307 0.2212886 0.2573687
IV 17,002,355 2,353.409 0.8187241 0.8372556
V 456,948,359 15,919.9 0.4062245 0.5932768
ARMA+GARCH
I 38,077,842 4908.317 0.1317732 0.1361043
II 93,164,156 5,861.041 0.2268906 0.2530479
III 56,736,538 3431.358 0.2183016 0.2395564
IV 3,837,969 1,356.005 0.4717387 0.5876807
V 553,535,870 16,671.04 0.4253909 0.5267857
Hybrid
I 36,177,293.39 4,652.507998 0.124905523 0.127347065
II 93017462.9 6169.871649 0.238845915 0.281375049
III 39,425,972.04 2,807.162152 0.178590549 0.206457204
IV 3,162,758.321 1,063.447725 0.369961347 0.384547602
V 493,400,639.5 16,787.20604 0.385329179 0.516025677