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2491Solve a Two-Feature No-Intercept OLS System 21For a no-intercept regression with X T X = [[4, 1], [1, 9]] and X T y = [10, 19], what is beta hat?机器学习简单数值题未尝试免费2492Why Feature Scaling Helps Gradient Descent More Than Closed Form 22Why is feature scaling often crucial for gradient-descent training of OLS even though the closed-form solution itself is scale-equivariant?机器学习简单essay未尝试免费2493Projection Error Is Orthogonal to the Fitted Subspace 23Why is y - X beta hat orthogonal to every fitted vector Xv?机器学习中等derivation未尝试面试订阅2494Centered Simple Regression Through the Origin 24After centering x and y in simple regression with an intercept, what optimization problem remains for the slope?机器学习中等derivation未尝试面试订阅2495When OLS Predictions Are Unique 25Even if the coefficient vector is not unique, why is the OLS fitted prediction X beta hat still unique?机器学习困难derivation未尝试面试订阅