y = data.price.values
X = data.drop('price',axis = 1)

from sklearn.cross_validation import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)
X_train






from sklearn.linear_model import Ridge
clf = Ridge(alpha=1.0)
clf.fit(X_train, y_train)
clf.coef_






RMSE_train = rmse(y_train, clf.predict(X_train))
RMSE_test = rmse(y_test, clf.predict(X_test))
print(rmse(y_train, clf.predict(X_train)), rmse(y_test, clf.predict(X_test)))