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Journal of Big Data

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
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