I want to build a machine learning model using the caret package in R. Some of the features in my dataset are dummies taking the value 0 or 1. I would like to know which resampling methods can be used in the presence of dummy variables.
k-fold cross-validation does not seem to be an option as explained in this post. I could potentially use leave-one-out cross-validation; however, this seems to be too expensive when N is large (my dataset has 100000+ observations).
Are there any suitable resampling methods in the presence of dummies and large N?