Optimal alpha jupyter

ridge2 = Ridge(alpha = 4, normalize = True)
ridge2.fit(X_train, y_train)             # Fit a ridge regression on the training data
pred2 = ridge2.predict(X_test)           # Use this model to predict the test data
print(pd.Series(ridge2.coef_, index = X.columns)) # Print coefficients
print(mean_squared_error(y_test, pred2))          # Calculate the test MSE

Source: science.smith.edu

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