House_Price_26.py

from sklearn.linear_model import Ridge
from sklearn.metrics import mean_squared_error

# different alpha values
alphas = [0.01, 0.1, 0.3, 1, 3, 5, 10, 15, 20]

for a in alphas:

    lr = Ridge(alpha=a)
    
    lr.fit(X_train,y_train)
    
    rmse = np.sqrt(mean_squared_error(y_test,lr.predict(X_test)))
    print('For Alpha = ',a,', RMSE = ',rmse)