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< travis-ci> saksham189/mlpack#32 (br - a26e58d : Saksham Bansal): The build is still failing.
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< soonmok> Hi I have a question about the tutorial example of ann (used "thyroid_train")
< soonmok> According to description of dataset (http://archive.ics.uci.edu/ml/machine-learning-databases/thyroid-disease/ann-Readme), this dataset has 21 attributes (15 binaries, 6 continuous)
< soonmok> but the example code train model with the partition of the whole data (15 binaries, 3 continuous), and this model predict 3 continuous attributes with the classification value
< soonmok> I think this model should use 21 attributes and predicts only classification value.
< soonmok> I'm talking about this tutorial (http://www.mlpack.org/docs/mlpack-git/doxygen/anntutorial.html)
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< travis-ci> saksham189/mlpack#33 (br - 7808d19 : Saksham Bansal): The build is still failing.
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< soonmok> I'm trying to run this code "DigitRecognizer.cpp". In this code, it import "mlpack/core/optimizers" but there is no optimizer in mlpack core directory. where can i find this ?
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< travis-ci> saksham189/mlpack#34 (br - d77010d : Saksham Bansal): The build was fixed.
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< jenkins-mlpack2> Project docker mlpack nightly build build #195: STILL UNSTABLE in 4 hr 4 min: http://ci.mlpack.org/job/docker%20mlpack%20nightly%20build/195/
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< ronit> Hello ,I am interested in contributing to mlpack and i have installed mlpack. Can someone please guide me on what i could do next ?
< soonmok> There is a tutorial on mlpack site.
< ronit> thank you .Ill look into the tutorials.
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< ja_> Hey
< ja_> I had a query regarding the ML Pack's latest version
< ja_> Anybody there to help?
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< rcurtin> ja_: what is the query?
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< coatless> exit
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< rcurtin> soonmok: sorry, didn't see your questions didn't get answered
< rcurtin> for DigitRecognizer.cpp, that should be using ensmallen, not mlpack/core/optimizers anymore
< rcurtin> (I am opening an issue for that now)
< rcurtin> it should be pretty easy to adapt that code just for your use by switching the include file names
< rcurtin> for thyroid_train.csv, I think that the dataset used there has the last three columns one-hot encoded, so taking the labels works okay there
< rcurtin> zoq: do you know more about thyroid_train.csv? the copy in src/mlpack/tests/data/ doesn't have one-hot encoded labels, so maybe we should change it (or change the tutorial code)?
< rcurtin> also, I think that the mlpack-bot is working for marking stale issues... but since I updated all the labels just a day or two ago, that counts as activity, so nothing will be marked as stale for a while
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< zoq> rcurtin: Do I remove the unanswered label or will the bot do that for me?
< zoq> rcurtin: soonmok: We should use another dataset.
< rcurtin> zoq: hmm, I'm not sure on this one. we could have the bot remove 'unanswered' as soon as some response is given
< rcurtin> but it might remove the 'unanswered' tag too early
< zoq> Okay, so I guess one from the contribution team will remove the label.
< rcurtin> yeah. let's see how the labels work as time goes on
< rcurtin> my thought was, "I'll try to get something working first, instead of trying to get the labels perfect the first time"
< rcurtin> so, I figure, as time goes on, we'll realize that some labels are more or less useful and we can adapt them as we go to come to a better solution
< zoq> ah, that sounds like a good idea
< rcurtin> I think I am basically done with the initial version of mlpack-bot
< rcurtin> so now I can prepare to start debugging it for the next N years ;)
< zoq> :)
< rcurtin> uh-oh
< rcurtin> well there's the first bug to debug :)
< zoq> :)
< zoq> at least we know that the bot can merge something :)
< rcurtin> I wasn't planning on having the bot do the merging, since it might accidentally merge something where more discussion was wanted
< rcurtin> just the approving
< rcurtin> I had to give it permissions to the repository so its approvals would show up as though it was part of the members of the repository
< rcurtin> but I think the likelihood of a bug where it modifies the code is very very small :)
< rcurtin> ok... now it checks to see if it already approved...
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< na_> Hi.
< zoq> na_: Hello there!
< rcurtin> na_: you must be ja_ from earlier :)
< rcurtin> feel free to leave questions here if nobody is here; someone will answer eventually and then you can check the log at http://www.mlpack.org/irc/
< na_> Okay, sure. Thanks!'
< na_> I got my doubt clarified through my friend, though
< na_> Thanks, again!
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< rcurtin> na_: great!
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