write a function to calculate mse in matlab

To write a function to calculate Mean Squared Error (MSE) in MATLAB, you can follow these steps:

  1. Declare a function with the desired name (e.g., calculateMSE) and input arguments.
  2. Inside the function, compute the square difference between the predicted values and the actual values.
  3. Calculate the mean of the squared differences.
  4. Return the mean squared error.

Here is an example implementation:

main.m
function mse = calculateMSE(actual, predicted)
    % Step 1: Declare the function and input arguments
    
    % Step 2: Compute the squared difference between predicted and actual values
    squaredDiff = (predicted - actual).^2;
    
    % Step 3: Calculate the mean of the squared differences
    meanSquaredDiff = mean(squaredDiff);
    
    % Step 4: Return the mean squared error
    mse = meanSquaredDiff;
end
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You can now call this function by passing in the actual and predicted values as arguments:

main.m
actual = [1, 2, 3, 4, 5];
predicted = [2, 3, 4, 5, 6];

mse = calculateMSE(actual, predicted);
disp(mse);
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This will output the mean squared error.

Note: Make sure to adjust the input arguments and calculateMSE function according to your specific requirements.

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