There is an equation that describes the cost function of Ridge, where j runs from 0 to p. So if p is 3, it means the linear model reads y=w0 + w1*xl+w2*x2 +w3*x3. wo is the intercept or rather bias, wl, w2 and w3 makes the slope of the plane. Now, assume p= 1, so this turns into your usual single-variate linear model. Work out the gradient descent by hand. M Σ (n − w)² = Ï (n − Ĺ w₁ x zu )³² +1 Σω - +) i=1 j=0 j=0 Cost function for ridge regression
There is an equation that describes the cost function of Ridge, where j runs from 0 to p. So if p is 3, it means the linear model reads y=w0 + w1*xl+w2*x2 +w3*x3. wo is the intercept or rather bias, wl, w2 and w3 makes the slope of the plane. Now, assume p= 1, so this turns into your usual single-variate linear model. Work out the gradient descent by hand. M Σ (n − w)² = Ï (n − Ĺ w₁ x zu )³² +1 Σω - +) i=1 j=0 j=0 Cost function for ridge regression
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter7: Analytic Trigonometry
Section7.6: The Inverse Trigonometric Functions
Problem 93E
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PLEASE SHOW WORK IN CLEAR HANDWRITING. MESSY HANDWRITING IS NOT ALLOWED
![a) There is an equation that describes the cost function of Ridge, where j runs from 0 to p. So if p is 3, it
y=w0+wl*xl+w2*x2+w3*x3. w0 is the intercept or rather bias, wl, w2
means the linear model reads
and w3 makes the slope of the plane.
Now, assume p= 1, so this turns into your usual single-variate linear model. Work out the gradient
descent by hand.
P
Σ( - ² - Σ (n -Ĺ‚× 2)² + x Ĺ²
j=0
Cost function for ridge regression
b) With the gradient descent, now please write down update rule
A simple update rule
• dy = f(x+h)-f(x).
.
dy=dxdx
Then, f(x + h) = dy+dx+f(x)
• Or rather, f(x₁) = x+dx+f(x₂)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fbd37214d-d9f3-4cec-9a4a-f5d72a5872c4%2F9d693397-3ede-48ce-b677-df07dafc9e3a%2Fggh36ss_processed.jpeg&w=3840&q=75)
Transcribed Image Text:a) There is an equation that describes the cost function of Ridge, where j runs from 0 to p. So if p is 3, it
y=w0+wl*xl+w2*x2+w3*x3. w0 is the intercept or rather bias, wl, w2
means the linear model reads
and w3 makes the slope of the plane.
Now, assume p= 1, so this turns into your usual single-variate linear model. Work out the gradient
descent by hand.
P
Σ( - ² - Σ (n -Ĺ‚× 2)² + x Ĺ²
j=0
Cost function for ridge regression
b) With the gradient descent, now please write down update rule
A simple update rule
• dy = f(x+h)-f(x).
.
dy=dxdx
Then, f(x + h) = dy+dx+f(x)
• Or rather, f(x₁) = x+dx+f(x₂)
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