1-Change this code from Matlab to Phython:* Compute and display initial cost and gradient for regularized logistic regression[cost, grad] = costFunctionReg (initial_theta, x, y, lambda);fprintf ('Cost at initial theta (zeros): %f\n', cost);28 fprintf ('Expected cost (approx) : 0.693\n');29 fprintf('Gradient at initial theta (zeros) - first five values only:\n');30 fprintf (' %f \n', grad (1:5));31 fprintf ('Expected gradients (approx)fprintf (' 0.0085\n 0.0188\n 0.0001\n 0.0503\n 0.0115\n');33 % Compute and display cost and gradient with all-ones theta and lambda = 10test_theta[cost, grad] =24252627first five values only:\n');32ones (size (X, 2),1);costFunctionReg (test_theta, X, y, 10);343510): %f\n', cost);36 fprintf ('\nCost at test theta (with lambda37 fprintf ('Expected cost (approx) : 3.16\n');38 fprintf('Gradient at test theta39 fprintf (' %f \n', grad (1:5));fprintf ('Expected gradients (approx)first five values only:\n');40first five values only:\n');41fprintf (' 0.3460\n 0.1614\n 0.1948\n 0.2269\n 0.0922\n');

function featureNormalize(x) rows = size(x,1) cols = size(x,2) μ = mean(x,1) σ = std(x,1) xNorm =…

printf('Cost at initial theta (zeros): %f\n', cost); printf('Expected cost (approx) : 0.693\n'); printf('Gradient at initial theta (zeros) - first five values only:\n'); printf (' %f \n', grad (1:5)); printf('Expected gradients (approx) - first five values only: \n'); printf(' 0.0085\n 0.0188\n 0.0001\n 0.0503\n 0.0115\n'); sCompute and display cost and gradient with all-ones theta and lambda est_theta = ones (size (X, 2),1); cost, grad] = costFunctionReg (test_theta, X, y, 10); printf('\nCost at test theta (with lambda = 10): %f\n', cost); printf('Expected cost (approx) : 3.16\n'); printf('Gradient at test theta - first five values only:\n'); printf(' f \n', grad (1:5)); printf('Expected gradients (approx) printf(' 0.3460\n 0.1614\n 0.1948\n 0.2269\n 0.0922\n'); = 10 first five values only:\n');

printf('Cost at initial theta (zeros): %f\n', cost); printf('Expected cost (approx) : 0.693\n'); printf('Gradient at initial theta (zeros) - first five values only:\n'); printf (' %f \n', grad (1:5)); printf('Expected gradients (approx) - first five values only: \n'); printf(' 0.0085\n 0.0188\n 0.0001\n 0.0503\n 0.0115\n'); sCompute and display cost and gradient with all-ones theta and lambda est_theta = ones (size (X, 2),1); cost, grad] = costFunctionReg (test_theta, X, y, 10); printf('\nCost at test theta (with lambda = 10): %f\n', cost); printf('Expected cost (approx) : 3.16\n'); printf('Gradient at test theta - first five values only:\n'); printf(' f \n', grad (1:5)); printf('Expected gradients (approx) printf(' 0.3460\n 0.1614\n 0.1948\n 0.2269\n 0.0922\n'); = 10 first five values only:\n');

Operations Research : Applications and Algorithms

4th Edition

ISBN:9780534380588

Author:Wayne L. Winston

Publisher:Wayne L. Winston

Chapter15: Deterministic Eoq Inventory Models

Section15.2: The Basic Economic Order Quantity Model

Problem 15P

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