You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I was wondering if there was any heuristics on choosing a model structure for different types / sizes of datasets. For instance, if I had a standard corporate dataset with 20,000 rows and 15 columns, are there any sure-fire methods / parameters I should be using? Are there any clear do's or dont's in certain situations?
The text was updated successfully, but these errors were encountered:
Hi @AnotherSamWilson, thanks for your question. We think the default settings should be fine for your dataset, but we've actually been working on a paper that discusses various heuristics/diagnostics for choosing model parameters. We'd be happy to share it, if you give us your email address (mine is R.Lall@lse.ac.uk).
Hi,
I was wondering if there was any heuristics on choosing a model structure for different types / sizes of datasets. For instance, if I had a standard corporate dataset with 20,000 rows and 15 columns, are there any sure-fire methods / parameters I should be using? Are there any clear do's or dont's in certain situations?
The text was updated successfully, but these errors were encountered: