Question 6
Consider the following code:
import numpy as npfrom sklearn.linear_model import LinearRegressionX = np.array([[1, 1], [1, 2], [2, 2], [2, 3], [2, 1], [3, 3]])# y = 1 * x_0 + 2 * x_1 + 3y = np.dot(X, np.array([1, 2])) + 3
reg1 = LinearRegression(fit_intercept = False).fit(X, y)s1 = reg1.score(X, y)
reg2 = LinearRegression(fit_intercept = True).fit(X, y)s2 = reg2.score(X, y)Which of the following is more likely to be true?