On Thu, Aug 23, 2018 at 03:06:48PM +0200, Anisa Llaveshi wrote: > Dear Ryan, > > Thank you for your quick response. I double checked and I am afraid that is > not the case. The matrix that I am providing as input to the model is a 1xN > matrix. I explicitly check the number of rows (1) and the number of columns > (N) of the matrix. The model would not even allow that because the labels > provided to the model is a row vector (rowvec) of N columns so the > dimensions would not match. > > Please let me know in case you think I am missing something or if you have > another idea of what might be going on.
Hi Anisa, It turns out you aren't missing anything at all. I took a look at the linear regression implementation and was surprised to see that it actually is trying to form an NxN matrix, whereas for linear regression it should only be necessary to form a dxd matrix. I spent a little time this evening reimplementing the code and have opened a pull request to fix it: https://github.com/mlpack/mlpack/pull/1500 You can either work directly off that branch, wait for another release, or copy the modified linear_regression.cpp file into your codebase. But now for your problem with 200k points, it should be blazing fast (like 0.005s to solve the system, minus data loading time). So you should be able to scale much more. Sorry for the error! I hope that this helps out, and if not, just let me know. Thanks, Ryan -- Ryan Curtin | "The enemy cannot press a button... if you have [email protected] | disabled his hand." - Sgt. Zim _______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
