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Table 68 Modes of RF tuned hyperparameter values for experiments with the information theft dataset

From: IoT information theft prediction using ensemble feature selection

Parameter name Value
bootstrap False
class_weight balanced_subsample
criterion gini
max_depth 8
max_features log2
min_impurity_decrease 0.00016
min_samples_leaf 2
min_samples_split 2
n_estimators 155
  1. Parameter values for classifier yielding best results in terms of AUC