cost function in matlab

To create a cost function in MATLAB, you can define a function that calculates the error or loss between the predicted and actual values. Here's an example of how you can implement a simple mean squared error (MSE) cost function:

main.m
function cost = cost_function(actual, predicted)
    % Calculate the error between actual and predicted values
    error = actual - predicted;
    
    % Calculate the mean squared error
    mse = mean(error.^2);
    
    % Return the cost (MSE)
    cost = mse;
end
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In this example, the cost_function takes two input arguments: actual and predicted, which represent the actual and predicted values, respectively. It calculates the error by subtracting the predicted values from the actual values. Then, it squares the error values, calculates the mean, and returns the mean squared error as the cost.

You can use this cost function in an optimization algorithm or any other application where you need to evaluate the performance of your prediction model.