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/
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< jeffin143> is there any function in Mlpack , which tell whether a feature is categorical or continuous ?
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< jenkins-mlpack2> Project docker ensmallen nightly build build #36: STILL FAILING in 48 min: http://ci.mlpack.org/job/docker%20ensmallen%20nightly%20build/36/
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< jenkins-mlpack2> Yippee, build fixed!
< jenkins-mlpack2> Project docker mlpack nightly build build #477: FIXED in 3 hr 15 min: http://ci.mlpack.org/job/docker%20mlpack%20nightly%20build/477/
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< rcurtin> jeffin143: if you loaded the matrix with a DatasetInfo, then you can just use datasetInfo.Type(i) where i is the index of the dimension
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< travis-ci> mlpack/mlpack#8081 (master - 916f9e8 : Ryan Curtin): The build passed.
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< zoq> Not sure I like the name "Plain".
< zoq> Btw. the timeout isn't 240 minutes, it's 360 minutes.
< rcurtin> zoq: looks nice!
< rcurtin> the only drawback I see is that with such a huge build timeout, it takes away the pressure for us to make mlpack compile more efficiently :-D
< zoq> Good point :), you can limit the runtime, so maybe this is something we should do. At the end we still have the jenkins matrix builds, which I think are often more helpful, at least in the long run.
< rcurtin> that'
< rcurtin> that's true
< rcurtin> I don't see a need to actually limit the runtime for Azure; at the current time I don't think any of us have any time to really go through and profile and accelerate the build itself anyway :)
< zoq> True, build time that is; test time is something else, I like to keep that time down as much as it makes sense.
< rcurtin> yeah, test time is definitely a higher priority
< rcurtin> and also an easier issue to solve usually :)
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< rcurtin> I'll release 3.2.1 later today or tomorrow unless anyone thinks we should wait on a PR or something
< zoq> rcurtin: Sounds good to me.
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