oem for real data analysis
LauraTurbatu opened this issue · comments
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 ?
Please show a reproducible example of any errors