Please Fill Blanks Clearvars Clc Addpath Generation Addpath Basicblocks Addpath Algorit Q43779691
Please fill the blanks:
clearvars
clc
addpath(‘../Generation’)
addpath(‘../Basic_blocks’)
addpath(‘../Algorithms’)
% Loading scenarios
% ===========================
scenario=1;
[data_class set_up]=scenarios_classification(scenario);
% Definition of the problem
%===================================
loss_logistic_L2 = ——————————;
grad_logistic_L2 = ——————————;
hess_logistic_L2 = @calculation_Hessian_logistic;
% Solution of the empirical risk using CVX
%=========================================
x_L2_cvx=solver_cvx(——————–);
loss_opt=loss_logistic_L2(set_up.Niter_train,set_up.Utrain(:,1:set_up.M+1),x_L2_cvx,set_up.ytrain(:,1),set_up.Lambda);
% Gradient descent
out_gd =grad_FOM(set_up,@(N,A,x,y,lambda)grad_logistic_L2(N,A,x,y,lambda));
S =plot_surface(set_up,loss_logistic_L2,x_L2_cvx);
close (figure(2))
figure(1),hold,
plot(out_gd(1,:),out_gd(2,:),’g’,’LineWidth’,3),hold off
loss_grad=eval_loss(out_gd,set_up,@(N,A,x,y,lambda)loss_logistic_L2(N,A,x,y,lambda));
% Newton algorithm
out_hess =grad_SOM(set_up,@(N,A,x,y,lambda)grad_logistic_L2(N,A,x,y,lambda),@(N,A,x,y,lambda)hess_logistic_L2(N,A,x,y,lambda));
S =plot_surface(set_up,loss_logistic_L2,x_L2_cvx);
close (figure(2))
figure(1),hold,
plot(out_hess(1,:),out_hess(2,:),’g’,’LineWidth’,3),
plot(out_gd(1,:),out_gd(2,:),’r’,’LineWidth’,3),
hold off
loss_hess=eval_loss(out_hess,set_up,@(N,A,x,y,lambda)loss_logistic_L2(N,A,x,y,lambda));
pause
% Plot of learning curves
plot(1:set_up.Niter_train,10*log10(sum((loss_grad-loss_opt*ones(1,set_up.Niter_train)).^2,1)),’b’,’LineWidth’,3),
hold
plot(1:set_up.Niter_train,10*log10(sum((loss_hess-loss_opt*ones(1,set_up.Niter_train)).^2,1)),’r’,’LineWidth’,3),
hold off
grid
xlabel(‘Iterations’)
ylabel(‘MSE’)
title(‘Logistic L2 Algorithm’)
Expert Answer
Answer to Please fill the blanks: clearvars clc addpath(‘../Generation’) addpath(‘../Basic_blocks’) addpath(‘../Algorithms’) % Loa…
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