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Table 69 Modes of XGBoost tuned hyperparameter values for experiments with the information theft dataset

From: IoT information theft prediction using ensemble feature selection

Parameter name

Value

n_estimators

100

min_child_weight

1

max_depth

8

learning_rate

0.30000

gamma

None

  1. “None” value indicates default value of hyperparameter is optimal; parameter values for classifier yielding best results in terms of AUPRC