[mlpack-git] [mlpack/mlpack] Density Estimation Tree made sparse-enabled (#802)
Ryan Curtin
notifications at github.com
Tue Nov 1 15:21:49 EDT 2016
Merge done, thanks for the contribution! I like the idea about making it easier to use either dense or sparse types depending on the given filename. I think we will need to think about it additionally though, so maybe it is worth opening a ticket for or something. For instance, if I pass in "coordinate_list.csv", I can either load it as a 3xN dense matrix or an RxC sparse matrix... I can't autodetect which is right. In the context of a C++ program, it is probably better to let the user select what they want by using either `data::Load<arma::mat>()` or `data::Load<arma::sp_mat>()`. But for the command-line programs, it would be nice if the user had a way to specify whether their matrix was sparse or dense and use the correct type then (`boost::variant` could be used there, or just some other template solution). I wonder if maybe it is easier to allow the user to specify file type by appending `:sparse` or `:dense` to their filename, like `-i coordinate_list.csv:sparse`. Anyway, maybe this is discussion for another place. I am open to ideas as long as they are clean, as always. :)
--
You are receiving this because you are subscribed to this thread.
Reply to this email directly or view it on GitHub:
https://github.com/mlpack/mlpack/pull/802#issuecomment-257666583
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://mailman.cc.gatech.edu/pipermail/mlpack-git/attachments/20161101/7df764ef/attachment.html>
More information about the mlpack-git
mailing list