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Table 62 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
max_depth 43
min_child_weight 0.01000
reg_lambda 0
subsample 0.58748
  1. Parameter values for classifier yielding best results in terms of AUC