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reduce random forest param grid

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Alexis REVELLE 2024-03-19 11:43:44 +00:00
parent 9e5e364aa3
commit ee86fcaf84
1 changed files with 5 additions and 6 deletions
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11
utils_ml.py
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@ -281,12 +281,11 @@ def pipeline_randomF_benchmark(X_train, y_train, X_test, y_test, model_result):
def pipeline_randomF_cv(X_train, y_train, X_test, y_test, model_result): def pipeline_randomF_cv(X_train, y_train, X_test, y_test, model_result):
y_train = y_train['y_has_purchased'] y_train = y_train['y_has_purchased']
param_grid = { param_grid = {
'randomF_cv__n_estimators': [100, 200, 300], 'randomF_cv__n_estimators': [100, 300],
'randomF_cv__max_features': ['sqrt', 'log2', None], 'randomF_cv__max_features': ['sqrt', 'log2'],
'randomF_cv__min_samples_split': [2, 5, 10], 'randomF_cv__min_samples_split': [2, 10],
'randomF_cv__min_samples_leaf': [1, 2, 4], 'randomF_cv__min_samples_leaf': [1, 4],
'randomF_cv__bootstrap': [True, False], 'randomF_cv__class_weight': [weight_dict]
'randomF_cv__class_weight': [None, weight_dict]
} }
pipeline = Pipeline(steps=[ pipeline = Pipeline(steps=[
('preprocessor', preproc), ('preprocessor', preproc),