from sklearn.linear_model import Ridge
from sklearn.selection_model import GridSearchCV
#Create a dictionary of parameter values:
Parameter1=[{'alpha':[0.001,0.1,1, 10, 100, 1000,10000,100000,100000],'normalize':[True,False]}]
#Create a ridge regions object:
Grid1=GridSearchCV(Ridge(),Parameter1,cv=4)
Grid1.fit(x_data,y_data)
Grid1.best_estimator_
scores=Grid1.cv_results_
scores['mean_test_score']