grid-search

.py

# unite the features and classifier together
pipe = Pipeline([('features', features),
                 ('clf',clf)
                 ])
                 
# create grid 
param_grid = { 
    'n_estimators': [200, 300, 400],
    'max_features': ['auto', 'sqrt', 'log2'],
    'max_depth' : [4,6,8,10,20],
    'criterion' :['gini', 'entropy']
}

# apply grid to model
search = GridSearchCV(pipe, param_grid, cv=2).fit(X, y)