train model using cvpartition

In this project, i am required to investigate the effectiveness of the logistic regression classifier in heart disease detection

i have to do this: function [theta, lambda] = trainLRModel(x, y, lambda_values)

by using cvpartition. and applies 10-fold cross validation to choose the best lambda value among lambda_values.

how can i use cvpartition with my logistic regression classifier model ?

this is my code so far

%% ******************* Loading Data **********************

data = xlsread('heart.csv');

disp('The dataset was loaded sucessfully!');

X = data(:,1:end-1);% features

y = data(:,end);% class labels

%disp(X);

%disp(y);

%disp(data);

m = size(X,2);

%% *******************feature Normalization**************************

for i=1:m,

X(:,i) = featureNormalization(X(:,i));

end

%disp(X);

%% ****************** Calculate Cost and Gradient *******************

lambda = 1;

theta = zeros(size(X, 2), 1);

%disp(size(initial_theta));

%X = [ones(size(X,1),1) , X];

%disp(size(X));

[cost, grad] = computeLRCost(X, y, theta,lambda);

disp('The cost when theta values initialized to zeros');

disp(cost);

%% ******************* Learn Theta Values *******************

theta = learnLRTheta(X, y, lambda);

%disp (theta);

%% ******************* train LR Model *******************

lambda_values = [0 0.001 0.003 0.01 0.03 0.1 0.3 1 3 10 20 30 40]';

%[theta, lambda] = trainLRModel(X, y, lambda_values);