Restrict ypred in fitrgp function
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Giacomo Caporusso
el 29 de Jun. de 2023
Comentada: Giacomo Caporusso
el 3 de Jul. de 2023
I have a dataset where x is the independent variable and y is the dependent variable. I'm using the fitrgp function to model the response to the variable x given the values of y. I need to enforce fitrgp's ypred output to be between two values 'a' and 'b'.
How can I do?
Are there any options for fitrgp to enforce this constraint?
Thank you.
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Manas
el 29 de Jun. de 2023
Hi Giacomo,
There is no direct way to enforce constraints on the predicted values. You may use the following code to enforce the constraints.
ypred(ypred < a) = a; % Set values below 'a' to 'a'
ypred(ypred > b) = b; % Set values above 'b' to 'b'
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Cyrus Monteiro
el 29 de Jun. de 2023
The `fitrgp` function in MATLAB does not have a built-in option to enforce constraints on the predicted output (`ypred`) to be within a specific range. However, you can manually enforce this constraint after obtaining the predictions.
Here's an example of how you can enforce the constraint on `ypred` to be between two values, 'a' and 'b'
% Assuming you have already trained the Gaussian Process model using fitrgp
model = fitrgp(X, y);
% Obtain the predicted values
ypred = predict(model, X);
% Enforce the constraint on ypred to be between 'a' and 'b'
a = 0; % Lower bound
b = 1; % Upper bound
ypred_constrained = max(min(ypred, b), a);
In the code above, `ypred_constrained` is the predicted output (`ypred`) after enforcing the constraint to be between 'a' and 'b'. The `max` function limits the values of `ypred` to be less than or equal to 'b', and the `min` function ensures the values are greater than or equal to 'a'.
By applying this constraint manually, you can ensure that the predicted values (`ypred_constrained`) fall within the desired range.
More about the fitrgp here
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