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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