verne.freenode.net changed the topic of #mlpack to: http://www.mlpack.org/ -- We don't respond instantly... but we will respond. Give it a few minutes. Or hours. -- Channel logs: http://www.mlpack.org/irc/
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< naywhayare>
stephentu_: I'm a bit hung up on eigs_pair() and I need to wait on a response from the Armadillo maintainer
< naywhayare>
basically ARPACK (and LAPACK too) provides both symmetric and nonsymmetric versions
< naywhayare>
but eig_pair() uses the LAPACK overload for nonsymmetric matrices. so I feel like there should be eig_sym_pair() and eig_gen_pair() or something like this, but I want to wait on the Armadillo maintainer's thoughts before I finalize the API
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< stephentu>
naywhayare: cool no rush i'm a bit hung up on school
< stephentu>
naywhayare: as for the primal dual stuff, i want to fix the bug, how do i reproduce it?
< stephentu>
naywhayare: can i edit the gsoc 2015 wiki?
< stephentu>
w/ my proposals?
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< naywhayare>
stephentu: yeah, feel free
< naywhayare>
as for the bug you could reproduce by setting a random seed via math::RandomSeed() at the start of the test
< naywhayare>
print the seed
< naywhayare>
then when you get a seed that fails you can hardcode it
< naywhayare>
it looks like you should be able to find one relatively easily, I think, based on the failure rates in the matrix build
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< stephentu>
naywhayare: cool thanks
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< stephentu>
naywhayare: ok i added some ideas
< stephentu>
it'd be cool if somebody actually took me up on them :)
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< sahmed95>
Okay, so I finally compiled my first .cpp file implementing the simple tutorial :
< sahmed95>
can all these issues be solved by using make instead of compiling with g++ ?
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< sahmed95>
and can this be updated in the wiki ?
< udit_s>
sahmed95: yes, it can. Just build mlpack using cmake and make into a folder, say "build".
< udit_s>
in the folder you can run a method by using the "./bin/emst" command, by following the parameters required for that method, as noted in it's documentation.
< udit_s>
To be clear, you would use "./bin/emst" for the "emst" method. :)
< sahmed95>
ohk,
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< stephentu>
sahmed95: i added a few new projects to the GSOC wiki if you are interested
< sahmed95>
yeah, I read the new ones. Implementing new algorithms sounds interesting (Fast k-centers Algorithm & Implementation, Manifold learning or l implementations of stochastic gradient descent and stochastic coordinate descent)
< sahmed95>
I m trying to get familiar with the codebase and trying to solve #380 (Log::Fatal backtrace)
< stephentu>
sahmed95: cool that will be useful for test failures
< stephentu>
sahmed95: let me know later on if you develop an interest in doing the latter two projects, i can provide some guidance
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< sahmed95>
Ok, so after some hours of going through the code and trying a manual way to figure out how to implement some sort of back trace, I gave up and started looking for libunwind examples. Found an awesome one at http://pastebin.com/0JW1Kh9R
< sahmed95>
I am new to C++ and can't decide whether this can be implemented in case of issue #380(Log::Fatal)
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< awhitesong1>
Hi, i asked in the list for the implementation of manifold learning algorithms a few days ago. So now i researched more on some of these algorithms. Also, currently going through the paper provided. I want to start implementing it now. If someone could guide me through this.
< awhitesong1>
Also regarding the issue #396, the problem was with the implementation of eigenvalue solver. Is there anything i can help in it now ?