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Table 60 Modes of DT tuned hyperparameter values for experiments with the theft dataset

From: IoT information theft prediction using ensemble feature selection

Parameter name Value
criterion gini
max_depth None
max_features sqrt
min_samples_leaf 7
  1. “None” value indicates default value of hyperparameter is optimal; parameter values for classifier yielding best results in terms of AUC