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Journal of Big Data

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
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