design the function function loss = detection_error_loss(t_hat, t) that computes the empirical detection-error loss f binary predictions t_hat in matlab

Here's an implementation of the requested function detection_error_loss(t_hat, t) that computes the empirical detection-error loss for binary predictions t_hat in MATLAB:

main.m
function loss = detection_error_loss(t_hat, t)
% Compute the empirical detection-error loss for binary predictions t_hat
% Inputs:
%   - t_hat: a binary vector representing the predicted labels
%   - t: a binary vector representing the true labels
% Output:
%   - loss: a scalar representing the empirical detection-error loss
%
    N = length(t);
    errors = (t_hat ~= t);
    loss = sum(errors) / N;
end
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The function first calculates the length of the binary vectors t_hat and t. Then it calculates a binary vector errors that represents the errors made by comparing the predicted labels with true labels. Finally, it calculates the mean of the errors, which represents the empirical detection-error loss.