x 1 Label (y) 2, 2.2 0, -0.1 -3, -2.5 1, 1 Fit the linear 1 regression model y = wx, using squared error. y = 1.5x₁ y = 2.9x₁ y = 0.9x, The answer is y = 0.9x1 1 Please use the concept of w = (XX^T)^-1 Xy Please show detailed steps x1Label (y) 2 2.2 0 -0.1 -3-2.5 1 1 4) Fit the linear regression model y = wx₁ using squared error. y = 1.5x1 ○ y = 2.9x1 y = 0.9x1

Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter7: Distance And Approximation
Section7.3: Least Squares Approximation
Problem 32EQ
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x 1 Label (y) 2, 2.2 0, -0.1 -3, -2.5 1,1 Fit the linear
1
regression model y = wx using squared error.
1
y = 1.5x₁ y = 2.9x₁ y = 0.9x, The answer is y = 0.9x1
1
Please use the concept of w = (XX^T) - 1 Xy Please
show detailed steps
x 1 Label (y)
2 2.2
0 -0.1
-3-2.5
1 1
4) Fit the linear regression model y = wx₁ using squared error.
y = 1.5x1
y = 2.9x1
y = 0.9x1
Transcribed Image Text:x 1 Label (y) 2, 2.2 0, -0.1 -3, -2.5 1,1 Fit the linear 1 regression model y = wx using squared error. 1 y = 1.5x₁ y = 2.9x₁ y = 0.9x, The answer is y = 0.9x1 1 Please use the concept of w = (XX^T) - 1 Xy Please show detailed steps x 1 Label (y) 2 2.2 0 -0.1 -3-2.5 1 1 4) Fit the linear regression model y = wx₁ using squared error. y = 1.5x1 y = 2.9x1 y = 0.9x1
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