classifier = linear_model.SGDClassifier(random_state = 0)
classifier.get_params().keys()
#out
['warm_start',
 'loss',
 'n_jobs',
 'eta0',
 'verbose',
 'shuffle',
 'fit_intercept',
 'epsilon',
 'average',
 'n_iter',
 'penalty',
 'power_t',
 'random_state',
 'l1_ratio',
 'alpha',
 'learning_rate',
 'class_weight']
#задаем грид 
parameters_grid = {
    'loss' : ['hinge', 'log', 'squared_hinge', 'squared_loss'],
    'penalty' : ['l1', 'l2'],
    'n_iter' : range(5,10),
    'alpha' : np.linspace(0.0001, 0.001, num = 5),
}

#запускаем грид
grid_cv = grid_search.GridSearchCV(classifier, parameters_grid, scoring = 'accuracy', cv = cv)