
194 Глава 6
>>> from sklearn.model_selection import GridSearchCV
>>> from sklearn.svm import SVC
>>> pipe_svc = make_pipeline(StandardScaler(),
... SVC(random_state=1))
>>> param_range = [0.0001, 0.001, 0.01, 0.1,
... 1.0, 10.0, 100.0, 1000.0]
>>> param_grid = [{'svc__C': param_range,
... 'svc__kernel': ['linear']},
... {'svc__C': param_range,
... 'svc__gamma': param_range,
... 'svc__kernel': ['rbf']}]
>>> gs = GridSearchCV(estimator=pipe_svc,
... param_grid=param_grid,
... scoring='accuracy',
... cv=10,
... refit=True,
... n_jobs=-1)
>>> gs = gs.fit(X_train, y_train)
>>> print(gs.best_score_)
0.9846153846153847
>>> print(gs.best_param ...