Question 7
Consider the following code:
import numpy as npfrom sklearn.linear_model import LinearRegressionX = np.array([[2, 3], [3, 4], [4, 5], [5, 6], [6, 7], [7, 8]])# y = 4 * x_0 + 5 * x_1 + 6y = np.dot(X, np.array([4, 5])) + 6
reg1 = LinearRegression(fit_intercept=True).fit(X, y)s1 = reg1.score(X, y)
reg2 = LinearRegression(fit_intercept=False).fit(X, y)s2 = reg2.score(X, y)Which of the following is true in this case?