Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

oem for real data analysis #16

Open
LauraTurbatu opened this issue Jun 8, 2018 · 1 comment
Open

oem for real data analysis #16

LauraTurbatu opened this issue Jun 8, 2018 · 1 comment

Comments

@LauraTurbatu
Copy link

LauraTurbatu commented Jun 8, 2018

I tryed using the oem package for variable selection for a quite large dataset, about 1 million observations and several variabales, around 60, both numerical and categorical. I used the sparse.model.matrix to transform the categorical to numerical, so I get some 1500 colons to the dataset. But then the X^TX is no longer invertible and so the oem function does not work. Can you recommend me what can I do when I want to do variable selection in a dataset with huge amount of lines and some categorical explanatory variables and also a few numerical ?

@jaredhuling
Copy link
Owner

Please show a reproducible example of any errors

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants