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Journal of Big Data

Table 67 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 AUPRC
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