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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< yvtheja> zoq, ping
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< zoq> yvtheja: Hello
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< yvtheja> zoq, Hi :)
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< yvtheja> zoq, How do we run all the tests?
< ranjan123> ,/bin/mlpack_test
< ranjan123> ./bin/mlpack_test
< yvtheja> ranjan123, Hey, Thanks :)
< zoq> right, you can also run a single TestSuite using bin/mlpack_test -t TestSuite. Take a look at: https://github.com/mlpack/mlpack/pull/544#issuecomment-191900999
< yvtheja> zoq, Gotcha ;)
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< kirizaki> zoq, did You ever build mlpack in VS15 (WIN32) ?
< zoq> kirizaki: yeah, yesterday to figure out how to solve: https://github.com/mlpack/mlpack/issues/534
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< kirizaki> jeez, it's so annoying :P
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< Dexter> Anyone here ?
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< kirizaki> up, hello
< kirizaki> yup*
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< csbqwerty> Thanks for helping out in installing mlpack yesterday. I went through the GSOC ideas list and IMPLEMENT TREE TYPES looks interesting. Are the necessary requirements for the other projects something which we can pick up while contributing?
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< yvtheja> zoq, ping
< yvtheja> zoq, I trying to write a test for KathirvalavakumarSubavathi initialization.
< yvtheja> zoq, As i understood from the bug, we need to initialize the weight using KathirvalavakumarSubavathi initialization and train them with Iris dataset and then we have to compare the results we get with the ones in the paper. Is it correct??
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< palashahuja> zoq, I have implemented dropconnect, please have a look https://github.com/palashahuja/mlpack/commit/d86f2908d172d9e38eb5a52b56600a8cc20dbc6a ..
< palashahuja> I am not sure what to do with layer traits ..
< rcurtin> palashahuja, do you mean that you don't understand what the layer traits are, or that you are not sure what they should be for dropconnect?
< palashahuja> I am not sure what they are for dropconnect .. ?
< rcurtin> okay; I can't help with what those values should be
< palashahuja> I am not sure, but I guess only the IsConnection parameter be true ..
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< zoq> yvtheja: yes, that's right
< yvtheja> zoq, Do we have to implement all the NM Structures mentioned in the paper??
< zoq> yvtheja: no one shold be enough
< yvtheja> zoq, okay thank you :)
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< palashahuja> does armadillo support add and assignment operator ?
< rcurtin> yes... see the armadillo documentation: http://arma.sourceforge.net/docs.html
< rcurtin> armadillo has a really nice API to work with (in my opinion, at least)
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< palashahuja> It is great ....
< zoq> palashahuja: yes, connection true
< palashahuja> thank you .
< palashahuja> I wiil send the PR asap
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< yvtheja> zoq, ping
< zoq> yvtheja: I'm always around :)
< yvtheja> zoq, haha
< yvtheja> zoq, Do we have any similar test files to KathirvalavakumarSubavathi ?
< yvtheja> zoq, I have implemented NN without any external libraries, so little confused if I need to do it in the same way or you are using anything diff
< zoq> The feedforward network test.app is similar, you could use the VanillaNetworkTest for the test, and check the return value of the optimizer.
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< ankur> hi, I have some doubt in building mlpack
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< zoq> yvtheja: You could also look at the NystroemMethodTest/GermanTest test. Btw. checkout https://github.com/mlpack/mlpack/issues/414
< zoq> ankur: Hello, can you tell us more about your problems?
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< ankur> after building mlpack I could not run allknn -h
< yvtheja> zoq, Sorry if it is a weird question, by optimizer you mean the cost function ?
< ankur> instead I have to write mlpack_allknn -h
< yvtheja> ankur, it's perfectly right :)
< yvtheja> ankur, I think the README have to be updated.
< ankur> also I could not find dataset.csv
< ankur> yes I think its old
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< yvtheja> zoq, are you mean the rmsprop one?
< zoq> ankur: Do you use the code from the master branch? If you use the latest release it's 'allknn'. It's a fictitious dataset.
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< yvtheja> <zoq> ankur: Do you use the code from the master branch? If you use the latest release it's 'allknn'. It's a fictitious dataset.
< zoq> yeah, the optimizer returns the MSE if you use MeanSquaredErrorFunction.
< yvtheja> zoq, gotcha, Thank you :)
< ankur> zoq on which branch I should work?
< ankur> Actually I am new to mlpack
< zoq> That depends, for GSoC I would use the master branch.
< ankur> zoq actually I am planning to apply for Essential Deep Learning Modules.
< ankur> what should be my course of action for planning to apply for this project
< ankur> any suggestions please.
< zoq> ankur: Here is a response to another prospective student about the deep
< ankur> thanks for help I will go through the discussion. :)
< zoq> ankur: Glad I could help.
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