rcurtin_irc changed the topic of #mlpack to: mlpack: a scalable machine learning library (https://www.mlpack.org/) -- channel logs: https://libera.irclog.whitequark.org/mlpack -- NOTE: messages sent here might not be seen by bridged users on matrix, gitter, or slack
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
<SuvarshaChennare> hello everyone
<SuvarshaChennare> im trying to implement ROC AUC
<SuvarshaChennare> but i have across a problem
<SuvarshaChennare> * to implement the ROC AUC, * ROC AUC metric
<SuvarshaChennare> the other metric classes have first classified and then computed the corresponding metric
<SuvarshaChennare> with ROC AUC i dont think its a good idea to classify within the Evaluate method
<SuvarshaChennare> because the models to be tested have different methods for classification
<SuvarshaChennare> what should I do?
<SuvarshaChennare> * to implement the ROC AUC, * ROC AUC metric for mlpack
<SuvarshaChennare> * to implement the ROC AUC, * ROC AUC metric for mlpack and Im almost done.
<SuvarshaChennare> Should I leave the classification out of the evaluate method?
<SuvarshaChennare> s/but i have across a problem/but I have come across a problem/
<SuvarshaChennare> * first classified with the data and then
<SuvarshaChennare> s/i/I/, s/dont/don't/
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
Guest35 has joined #mlpack
Guest35 has quit [Client Quit]
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
<heisenbuugGopiMT> Why is `memory check` failing? Am I doing something wrong, or will restarting the tests will work?
<shrit[m]> no this is an issue with Jenkins itself.
<heisenbuugGopiMT> Oh okay, then I think I am done with this pr, coz I was able to build mlpack successfully locally, but I didn't ran the tests
<heisenbuugGopiMT> So what's the solution here?
<heisenbuugGopiMT> And whats causing the issue?
<shrit[m]> I have no idea, maybe zoq do you have an idea what is happening with the memory check issues?
texasmusicinstru has quit [Remote host closed the connection]
<shrit[m]> Thank you very much I am going to give it a review of the builds are passing
<heisenbuugGopiMT> Also, I am not sure but should I add my name to the list of authors? It's not like I actually made changes to the core logic...
texasmusicinstru has joined #mlpack
<shrit[m]> Up to you, I would not add my name unless If I add a features or modified extensivley the file.
<shrit[m]> s/a//, s/extensivley/extensively/
<heisenbuugGopiMT> Yes, I don't think I should.
<heisenbuugGopiMT> Thank you.
<heisenbuugGopiMT> I will get on that issue which you opened, I think I might be able to complete it tonight.
<heisenbuugGopiMT> I would love to see mlpack becoming header only
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack
<zoq[m]1> > <@heisenbuug-5a298898d73408ce4f8241d7:gitter.im> https://github.com/mlpack/mlpack/pull/1454
<zoq[m]1> > Why is `memory check` failing? Am I doing something wrong, or will restarting the tests will work?
<zoq[m]1> Sometimes, the build node runs out of memory, adjusted some settings, let's see if that solves the problem.
<zoq[m]1> >
<heisenbuugGopiMT> oh okay, so basically it's azure's issue?
<heisenbuugGopiMT> Regarding `cosine_tree`, there is a part where we are iterating `boost::heap::priority_queue` but we cant do the same for `std::priority_queue`
<heisenbuugGopiMT> I mean we can't iterate over them using an iterator
<heisenbuugGopiMT> * an iterator, we have to pop the elements
<heisenbuugGopiMT> And since these functions are not modifying the queue anyways should I pass them as value and then pop them, so that it won't mess with original?
texasmusicinstru has quit [Remote host closed the connection]
texasmusicinstru has joined #mlpack