grid search.py

# Do grid search

from sklearn.model_selection import GridSearchCV

rf_classifier = RandomForestClassifier(random_state=0)

rf_model_pipeline = Pipeline(steps=[
    ('preprocessing', columns_transformer),
    ('rf_model', rf_classifier),
])

params_dict = {'rf_model__n_estimators' : np.arange(5, 100, 1), 'rf_model__criterion': ['gini', 'entropy'], 'rf_model__max_depth': np.arange(10, 200, 5)}

grid_search = GridSearchCV(rf_model_pipeline, params_dict, cv=10, n_jobs=-1)
grid_search.fit(X_train, y_train)