mean square error loss in matlab

main.m
function mse = mean_squared_error(y_true, y_pred)
% Calculates the mean squared error between two arrays
% y_true: true values array
% y_pred: predicted values array
% returns: mean squared error value

    % calculate the difference between true and predicted values
    error = y_true - y_pred;
    
    % square the error values
    squared_error = error.^2;
    
    % calculate the mean of squared error values
    mse = mean(squared_error);
    
end
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main.m
% true and predicted values
y_true = [3, -0.5, 2, 7];
y_pred = [2.5, 0.0, 2, 8];

% calculate mean squared error
mse = mean_squared_error(y_true, y_pred);

% print the result
fprintf('Mean squared error: %f\n', mse);
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main.m
Mean squared error: 0.375000
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