Can you convert the code written in knn below with logistic regression

clc;

clear;

close all;

% Load training data

train_men = dir(fullfile(['training\men\','*.jpg']));

train_images_men = [];

for i = 1:length(train_men)

file_name = strcat('training\men\',train_men(i).name);

image = imread(file_name);

re = reshape(image, [1 1296]);

train_images_men = [train_images_men; re];

end

train_women = dir(fullfile(['training\women\','*.jpg']));

train_images_women = [];

for i = 1:length(train_women)

file_name = strcat('training\women\',train_women(i).name);

image = imread(file_name);

re = reshape(image, [1 1296]);

train_images_women = [train_images_women; re];

end

train_images = [train_images_men; train_images_women];

train_labels = [zeros(length(train_images_men), 1); ones(length(train_images_women), 1)]; % 0 for men, 1 for women

train_images = double(train_images);

% Load test data

test_men = dir(fullfile(['testing\men\','*.jpg']));

test_images_men = [];

for i = 1:length(test_men)

file_name = strcat('testing\men\',test_men(i).name);

image = imread(file_name);

re = reshape(image, [1 1296]);

test_images_men = [test_images_men; re];

end

test_women = dir(fullfile(['testing\women\','*.jpg']));

test_images_women = [];

for i = 1:length(test_women)

file_name = strcat('testing\women\',test_women(i).name);

image = imread(file_name);

re = reshape(image, [1 1296]);

test_images_women = [test_images_women; re];

end

test_images = [test_images_men; test_images_women];

test_labels = [zeros(length(test_images_men), 1); ones(length(test_images_women), 1)]; % 0 for men, 1 for women

test_images = double(test_images);

% Subtract the mean 'face' before performing PCA

h = 36;

w = 36;

faces = (train_images)';

numFaces = size(faces, 2);

meanFace = mean(faces, 2);

faces = faces - repmat(meanFace, 1, numFaces);

% Perform Singular Value Decomposition

[u, d, v] = svd(faces, 0);

% Pick the principal components that capture 90% of data variance

eigVals = diag(d);

energy = cumsum(eigVals);

propEnergy = energy./energy(end);

percentMark = min(find(propEnergy > 0.9));