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Journal of Big Data

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
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