我正在尝试使用CVGridSearch为我的数据找到最佳参数
lasso = Lasso(random_state=0)
alphas = [0.5, 0.1 , 0.01 ]
max_iter = [1000, 2000, 3000]
tuned_parameters = [{'alpha': alphas , 'max_iter' : max_iter}]
n_folds = 5
clf = GridSearchCV(lasso, tuned_parameters, cv=n_folds, refit=False)
clf.fit(X_train, y_train.values.ravel())
运行代码时，它会显示以下警告信息
Best: 0.999998 using {'alpha': 0.1, 'max_iter': 1000}
Best: -2028.743734 using {'alpha': 0.1, 'max_iter': 1000}
/usr/local/lib/python3.6/site-
packages/sklearn/linear_model/coordinate_descent.py:492:
ConvergenceWarning: Objective did not converge. You might want to
increase the number of iterations. Fitting data with very small alpha
may cause precision problems.
ConvergenceWarning)
Best: -2241.410408 using {'alpha': 0.01, 'max_iter': 1000}
/usr/local/lib/python3.6/site-
packages/sklearn/linear_model/coordinate_descent.py:492:
ConvergenceWarning: Objective did not converge. You might want to
increase the number of iterations. Fitting data with very small alpha
may cause precision problems.
找到最高分数0.999998时，为什么CVGridsearch不停止？