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I would like to know why my system's RAM gets overloaded when I try to execute any of the parity metrics of your package. I have a Windows 10 Entreprise System, with 8 Gb RAM. My dataset has a size of 20 Mb. In R I get this message: "Error: no se puede ubicar un vector de tamaño 5.6 Mb".
I did the same excercise in Fedora and I had no issues (similar RAM specifications).
I attach an image of memory usage when I execute the function.
Thank you.
The text was updated successfully, but these errors were encountered:
thanks a lot for reporting the issue. This is not expected behavior. I am a little unsure about the exact reason; my tests on Windows with the included data sets do not exhibit any memory issues. One thing that comes to mind is to check encoding of variables supplied to a metric function (e.g., make sure that predicted probabilities are numeric, group variable is a factor with not too many levels, etc).
If your data are not sensitive, could you please share it along with a reproducible example? That way I can try to help you by checking what is happening there.
Hello.
I would like to know why my system's RAM gets overloaded when I try to execute any of the parity metrics of your package. I have a Windows 10 Entreprise System, with 8 Gb RAM. My dataset has a size of 20 Mb. In R I get this message: "Error: no se puede ubicar un vector de tamaño 5.6 Mb".
I did the same excercise in Fedora and I had no issues (similar RAM specifications).
I attach an image of memory usage when I execute the function.
Thank you.
The text was updated successfully, but these errors were encountered: