Glad I am not the only one. This seems like a task of memory, not author identification. How could this be used at test time?
10.000 users is meaningless on a social network with millions of accounts.
What about the static features (like account creation dates)? Aren't those overfitting with cross-validation? Would not learning curves be required when classifying on unseen future data (the reason d'etre of ML)?
10.000 users is meaningless on a social network with millions of accounts.
What about the static features (like account creation dates)? Aren't those overfitting with cross-validation? Would not learning curves be required when classifying on unseen future data (the reason d'etre of ML)?