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Journal of Big Data

Table 4 Models’ performances during the testing phase

From: Prediction of probable backorder scenarios in the supply chain using Distributed Random Forest and Gradient Boosting Machine learning techniques

Performance metric

GBM (with actual data)

GBM (with ranged data)

DRF (with actual data)

DRF (with ranged data)

LogLoss

0.098

0.029

0.036

0.042

AUC

0.795

0.946

0.787

0.959

Mean per class error

0.423

0.07

0.430

0.103

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