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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 means the linear model reads y = w0 + wl*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 Ë‹- - -‚³² −Ë (- - É ˜‚ × ²)*´- ‹ Ĺ – --Σ(Σώχος) Σ(v₁-9₁)² = w + 1 ² i=1 i=1 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 = d.dx Then, f(x + h) = x+dx+f(x) Or rather, f(x₁) = x+dx+f(x₂)

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 means the linear model reads y = w0 + wl*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 Ë‹- - -‚³² −Ë (- - É ˜‚ × ²)*´- ‹ Ĺ – --Σ(Σώχος) Σ(v₁-9₁)² = w + 1 ² i=1 i=1 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 = d.dx Then, f(x + h) = x+dx+f(x) Or rather, f(x₁) = x+dx+f(x₂)

Advanced Engineering Mathematics
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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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 means the linear model reads y = w0 + w1*xl +w2*x2 + w3*x3. w0 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 − v ² = Σ (u - Σ w‚ × x y)² + ^ Ĺ m² j=0 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 = d.dx Then, f(x + h) = x+dx+f(x) • Or rather, f(x₁) = 2X+dx+f(x₂)
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 means the linear model reads y = w0 + w1*xl +w2*x2 + w3*x3. w0 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 − v ² = Σ (u - Σ w‚ × x y)² + ^ Ĺ m² j=0 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 = d.dx Then, f(x + h) = x+dx+f(x) • Or rather, f(x₁) = 2X+dx+f(x₂)
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