design the function function out = mse_loss(t_hat, t) that computes the empirical mean square error loss of prediction t_hat in matlab

Here's an implementation of the function mse_loss:

main.m
function out = mse_loss(t_hat, t)
% Calculate the empirical mean square error loss between predicted and actual values
% Inputs:
%   - t_hat: the predicted values
%   - t: the actual values
% Output:
%   - out: the mean square error loss between t_hat and t

    % Calculate the difference between predicted and actual values
    diff = t_hat - t;
    
    % Calculate the square of the difference
    square_diff = diff .^ 2;
    
    % Calculate the mean of the square differences
    out = mean(square_diff);
end
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  • The function takes the predicted values t_hat and actual values t as inputs and returns the mean square error loss between them.
  • The diff variable stores the difference between each corresponding value of t_hat and t.
  • The square_diff variable calculates the square of the differences.
  • Finally, the out variable calculates the mean of the square differences using the mean function.

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