<rcurtin[m]>
do we have a guide anywhere on how to set up a local notebook server with xeus-cling? I think that all I need to do is start the correct docker image, but if we already have how to do this written down somewhere, it could save me a few minutes 😃
<zoq[m]>
But since mlpack is header only now, this can be simplified a lot.
<zoq[m]>
I can do this later.
<rcurtin[m]>
okay, so in this setup, I guess you are running jupyter locally and setting up the environment via that script?
<rcurtin[m]>
I am very not knowledgeable about notebooks, but I decided today is the day I am going to learn :)
<zoq[m]>
Correct, it will setup a conda env to run the instance.
<rcurtin[m]>
thanks, let me give it a shot and see what happens...
<rcurtin[m]>
maybe we should move that script to `tools/` with the other scripts? also I think the first line needs to be `#!/usr/bin/env bash` not `#!/usr/bin/env/bash` :)
<rcurtin[m]>
I still don't have everything working quite yet, but if you want, I can open a PR with that change (and any others I find I might need to get this working locally)
<rcurtin[m]>
I used the `continuumio/anaconda3` container, but I will try to find some newer version of this or something
<zoq[m]>
<rcurtin[m]> "I still don't have everything..." <- Sure, that works.
<zoq[m]>
rcurtin[m]: Yes, getting the correct dependencies is tricky.
<rcurtin[m]>
yeah, I see... it actually looks to me like xeus-cling is built against an older version of libstdc++... so I am going to try using an older anaconda container
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<Guest_ak>
mlpack python does not support gini and information gain. any work around for that?
<Guest_ak>
Team could you please help me on that
<rcurtin[m]>
the decision tree binding supports Gini impurity, but not information gain; you would either have to handwrite a binding yourself, or use C++
<Guest_ak>
mlpack python does not support choice of dimension selection ( multiple Random Dimension select )
<Guest_ak>
Any work around for that
<rcurtin[m]>
the bindings are a limited subset of mlpack's support; if you want access to everything mlpack does, you will have to use C++ 👍️
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<rcurtin[m]>
wow, it's impressive how long this script can take to run... conda has been `Examining conflict` for four hours now...
<zoq[m]>
Probably can’t find a solution, have seen this before.
<rcurtin[m]>
the status message keeps changing though, so I think it is making progress, just at a glacial pace 😃
<rcurtin[m]>
actually I found that even when using the binder link on https://github.com/mlpack/examples, after building the image, the kernel cannot actually evaluate anything, so maybe something is wrong with the regular image too?
<rcurtin[m]>
I'm still trying to build locally too
<zoq[m]>
I’ll check it later.
<rcurtin[m]>
I'll keep digging too because I want to learn a little bit, but don't feel obligated to respond or anything when I post about what I am finding 😃