Consider a data generating process consisting of i.i.d. random vectors X, 1 2 ... with with common Radon-Nikodym density Pe defined with respect to support specification measure v. A realization of x1,x2,... is a sequence of pattern vectors X1, X3, .... Each pattern vector x = [7,8] consists of a scalar desired response variable r ER and a 20-dimensional input pattern vector s {0,1}20. Assume that the loss function for learning is c(x;) for a learning machine with q-dimensional parameter vector 8. Which of the following is an expression for the expected loss E{c(8,0)}? Assume the support of is R. Assume the support of is S S {0,1}24 Choose 2 of the following choices by modifying the MATLAB code. Choice 1: E{c,)} = les Eres C([1,8], @)pe[r,s]>ds Choice 2: E{0,0)} = les resc{[r,s), 8)ds Choice 3: E{(0)} = sestre ([1,8], @)p:{[r,s]}dr Choice 4: E{c(8,4)} = (1) -C(X) Choice 5: E{c(,0)} = c(x,0)p (x)dv(x). ES Script C Reset DE MATLAB Documentation 1 Choiceids = [1 2]; 2 Choiceids = sort(Choiceids); 3 ChoiceidsDIM = length (Choiceids); 4 for i = 1:ChoiceidsDIM, 5 disp( ['Choice #', num2str(Choiceids(i)),' is an expression for the expected loss.']); 6 end; 7 Consider a data generating process consisting of i.i.d. random vectors X, 1 2 ... with with common Radon-Nikodym density Pe defined with respect to support specification measure v. A realization of x1,x2,... is a sequence of pattern vectors X1, X3, .... Each pattern vector x = [7,8] consists of a scalar desired response variable r ER and a 20-dimensional input pattern vector s {0,1}20. Assume that the loss function for learning is c(x;) for a learning machine with q-dimensional parameter vector 8. Which of the following is an expression for the expected loss E{c(8,0)}? Assume the support of is R. Assume the support of is S S {0,1}24 Choose 2 of the following choices by modifying the MATLAB code. Choice 1: E{c,)} = les Eres C([1,8], @)pe[r,s]>ds Choice 2: E{0,0)} = les resc{[r,s), 8)ds Choice 3: E{(0)} = sestre ([1,8], @)p:{[r,s]}dr Choice 4: E{c(8,4)} = (1) -C(X) Choice 5: E{c(,0)} = c(x,0)p (x)dv(x). ES Script C Reset DE MATLAB Documentation 1 Choiceids = [1 2]; 2 Choiceids = sort(Choiceids); 3 ChoiceidsDIM = length (Choiceids); 4 for i = 1:ChoiceidsDIM, 5 disp( ['Choice #', num2str(Choiceids(i)),' is an expression for the expected loss.']); 6 end; 7