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Table 95 Modes of XGBoost tuned hyperparameter values for experiments with the keylogging dataset

From: IoT information theft prediction using ensemble feature selection

Parameter name Value
max_depth 31
min_child_weight 0.01000
reg_lambda 10
subsample 0.61210
  1. Parameter values for classifier yielding best results in terms of AUPRC