This code first makes predictions using a regression model `reg`...

May 12, 2024 at 06:23 PM

predicted = reg.predict(X) mse = ((np.array(y)-predicted)**2).sum()/len(y) r2 = r2_score(y, predicted) print("MSE:", mse) print("R Squared:", r2)

This code first makes predictions using a regression model reg on the input data X. Then it calculates the Mean Squared Error (MSE) between the actual target values y and the predicted values, and then calculates the R-squared score between y and the predicted values. Finally, it prints out the MSE and R-squared values.

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