ChanServ changed the topic of #mlpack to: "mlpack: a fast, flexible machine learning library :: We don't always respond instantly, but we will respond; please be patient :: Logs at http://www.mlpack.org/irc/
< sreenik[m]>
I'm currently working on the PR. It will hopefully be over by the end of tonight.
< sreenik[m]>
I am going for dinner now, I'll be back in an hour or so. Please feel free to directly open an issue in the repo if you have any feedback :)
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< jeffin143>
rcurtin : umm not sure if you remember, but for scaler class the API is call scale.fit() and then scale.transform()
< jeffin143>
But if user calls transform () without it throws error since multiplication is not possible* and hence I have added a check , if the matrix is empty
< jeffin143>
Inform user to call fit() first, not sure if this is the right way to handle
< jeffin143>
Sorry typo : if user calls transform () without calling fit(), the api will break*
< rcurtin>
jeffin143: right, agreed, that sounds good to me
< rcurtin>
you *might* consider calling it Train() instead of Fit() so it matches the other mlpack classes (instead of imitating scikit), but I am not too picky
< jeffin143>
I agree with you, train sounds much better
< jeffin143>
Let's just go with train*
< rcurtin>
sounds good
< rcurtin>
:)
< akhandait>
sreenik[m]: Great work, I will take a detailed look at it tomorrow.
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< sreenik[m]>
akhandait: Sure
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< jeffin143>
zoq : I hope, adding images to blog website is not of an issue, if is it , let me know , I will just give a link instead of Saving it in repo.
< zoq>
jeffin143: Absolutely fine to add images to the repo.
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< gmanlan>
hi there, anybody knows if we have CNN in mlpack? I believe I've seen something but I'm not sure...
< sreenik[m]>
jeffin143: I am personally a fan of Tom memes. Had a laugh there :)
< gmanlan>
excellent, thanks!
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< abernauer>
rcurtin: Having some issues with the compiler when I try to wrap mlpack main in external "C"{}.
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< rcurtin>
abernauer: I can try and help but I would need more information
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< abernauer>
Actually I might not need to take that approach. Working through getting it to be callable in R.
< rcurtin>
note that from R you also will need to call all of the CLI::GetParam<> functions to set the CLI parameters that will be used by mlpackMain()
< rcurtin>
wrapping those may be a little more tricky---but I am not sure as I'm not really familiar with Rcpp
< abernauer>
Rcpp is cpp class that uses a lot of generic template programming.
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