Suppose that you have the following collection T of data points in two dimensions: x 4 1 12 3 3 2 4 y 1 2 B B R R B The picture below illustrates these points, together with the classifier if r+y-3> 0 then BLUE else RED, corresponding to the weight vector (1,1,3). 4. DO B 3 2 1 Classified red 1 2 3 4 A. Compute the value of the error function for this classifier: ET(w) = Σ PET p misclassified E Classified blue W₁Pr + W₂Py - Ws|
B. Compute the gradient of the error function with respect to the weight vector w. The gradient is a vector VE = (91,92,93) computed as follows: For a given weight vector and data point p = T let 1 8(P) if p is labelled RED in 7 but is classified BLUE by -1 if p is labelled BLUE in T but is classified RED by p is correctly classified by 0 if Then VE = S(p) (Pz. Py, -1) PET C. Compute the new weight vector after one step of gradient descent: w' = -8 VE where 8 = 0.1. D. How does the new weight vector w' classify the points? E. What is the value of the error function at the new weight vector w'?
Suppose that you have the following collection T of data points in two dimensions: x 4 1 12 3 3 2 4 y 1 2 B B R R B The
-
answerhappygod
- Site Admin
- Posts: 899604
- Joined: Mon Aug 02, 2021 8:13 am
Suppose that you have the following collection T of data points in two dimensions: x 4 1 12 3 3 2 4 y 1 2 B B R R B The
Join a community of subject matter experts. Register for FREE to view solutions, replies, and use search function. Request answer by replying!