Table 4 Training accuracy, precision, loss.

From: Traffic prediction in SDN for explainable QoS using deep learning approach

 

XGBoost

GBM

DRF

MSE

0.0000701

0.0000895

0.0000055

RMSE

0.008374838

0.009459834

0.002344221

LogLoss

0.00037684

0.000939903

0.0000318

Mean Per-Class Error

0.007575758

0

0

AUC

0.999999636

1

1

AUCPR

0.999999999

1

1

Gini

0.999999272

1

1

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