Open Access

Table B.2.

Hyper-parameters used in RandomForestClassifier.

Hyper-parameter Value
n_estimators 100
criterion gini
max_depth None
min_samples_split 2
min_samples_leaf 1
min_weight_fraction_leaf 0.0
max_features auto
max_leaf_nodes None
min_impurity_decrease 0.0
bootstrap True
oob_score False
n_jobs None
random_state 42
verbose 0
warm_start False
class_weight None

Notes. Hyper-parameters are listed with their default values as used in the RandomForestClassifier from scikit-learn.

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