design the function function t_hat= perceptron_predict(x, map_func, theta). the function returns the perceptron output t_hat, as a column vector of hard predictions applied to n inputs in matlab

The following code will design the function perceptron_predict(x, map_func, theta) in MATLAB that returns the perceptron output t_hat, as a column vector of hard predictions applied to n inputs.

main.m
function t_hat= perceptron_predict(x, map_func, theta)
% Input:
% x: the input dataset
% map_func: the mapping function used for transforming the input data 
% theta: the learned weights for the perceptron
% Output:
% t_hat: the predicted output of 'x' based on the trained perceptron model

% Transform the input data using the mapping function
x = map_func(x);

% Calculate the predicted output
t_hat = sign(x*theta);

end
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Here, map_func is a function that can be used to transform the input data. theta is the learned weights for the perceptron.

The function first applies the mapping function to the input dataset. It then calculates the predicted output using learned weights of the perceptron. The predicted output t_hatis returned as a column vector of hard predictions applied to n inputs.