Computer scienceData scienceMachine learningRegression

Introduction to regression

Choosing a regression model

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Imagine that you have several regression models to predict the value of the target attribute $Y$ from two inputs, $X_1$ and $X_2$ . You have the following dataset to evaluate them:

$X_1$	$X_2$	$Y$
-2	2	1.5
-1	1	1
0	0	0
1	-1	-0.5
2	2	9

Which model is the best in terms of the MSE score on the dataset above? If several models achieve the best performance, select all of them.

Hint

Input values as python lists:

X_1 = [-2, -1, 0, 1, 2]
X_2 = [2, 1, 0, -1, 2]
Y = [1.5, 1, 0, -0.5, 9]

To answer this question, first compute the predictions produced by each model. Then, compute the MSE score of each model by comparing the predicted values of the target with the real ones.

Select one or more options from the list

Y = 3*X_1 + 2*X_2

Y = -0.5 + 2*X_1 + 3*X_2

Y = 0.5 + 2*X_1 + 3*X_2

Y = 2*X_1 + 3*X_2

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