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Table 4 Hyperparameter settings of each model

From: Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning

Machine learning model

Hyperparameter settings

DT

Criterion: Gini

Splitter: best

max_depth: None

random_state: 42

RF

n_estimators: 100

criterion: Gini

max_depth: 5

random_state: 42

kNN

n_neighbors: 3

NB

Default parameters

MLP

hidden_layer_sizes: 100

activation: relu

alpha: 0.0001

batch_size: auto

learning_rate: constant

max_iter: 200