fitscalingrank in matlab

In MATLAB, there is no built-in function called fitscalingrank. However, if you are looking for a way to perform feature scaling on your data, you can use the normalize function.

The normalize function in MATLAB helps to scale the values of a dataset between a specified range or to z-scores. Here's an example of how you can use it:

main.m
% Sample data
data = [10, 20, 30, 40, 50];

% Normalize the data to the range [0, 1]
scaled_data = normalize(data, 'range');

% Display the scaled data
disp(scaled_data);
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Output:

main.m
0    0.2500    0.5000    0.7500    1.0000
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In the example above, we have a sample data array [10, 20, 30, 40, 50], and we use the normalize function to scale the values between 0 and 1. The result is displayed as [0, 0.25, 0.5, 0.75, 1].

You can also perform other types of scaling using the normalize function, such as z-scores. Here's an example:

main.m
% Sample data
data = [10, 20, 30, 40, 50];

% Normalize the data to z-scores
scaled_data = normalize(data, 'zscore');

% Display the scaled data
disp(scaled_data);
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Output:

main.m
-1.2649   -0.6325         0    0.6325    1.2649
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In the above example, we have used 'zscore' as the second argument in the normalize function to normalize the data to z-scores.

Remember to adjust the input parameters based on your specific needs.