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Getting hyper-parameters of models in Scikit-learn

Scikit-learn
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schedule Jul 1, 2022
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Solution

To get all the hyper-parameters of a model in Scikit-learn:

from sklearn.ensemble import RandomForestClassifier

model = RandomForestClassifier(max_depth=4)
model.get_params()
{'bootstrap': True,
'ccp_alpha': 0.0,
'class_weight': None,
'criterion': 'gini',
'max_depth': 4,
'max_features': 'auto',
'max_leaf_nodes': None,
'max_samples': None,
'min_impurity_decrease': 0.0,
'min_impurity_split': None,
'min_samples_leaf': 1,
'min_samples_split': 2,
'min_weight_fraction_leaf': 0.0,
'n_estimators': 100,
'n_jobs': None,
'oob_score': False,
'random_state': None,
'verbose': 0,
'warm_start': False}

Here, we see the default hyper-parameters of a random forest model.

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Published by Isshin Inada
Edited by 0 others
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