Github user erikerlandson commented on the issue:
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update - I'm consulting with some teammates about what it might mean to
also support Bayesian variations on split quality, since there has been a lot
of interest in the last few years
Github user erikerlandson commented on the issue:
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I think targeting 3.0 with a refactor makes the most sense. There's no way
to do this without making small breaking changes, but slightly larger changes
could clean up the design.
Github user srowen commented on the issue:
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Yeah I take your point that the trait Impurity already defines two methods,
only one of which is implemented for each of the subclasses. It's already a
funky design that probably should have been
Github user willb commented on the issue:
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@srowen @thunterdb this PR passes all tests and merges cleanly -- can you
take another look? It's been open for quite a while now.
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Is this still being considered?
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I agree with @felixcheung -- @srowen or @thunterdb, can you take a look at
this?
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@srowen @thunterdb any more thoughts on this?
how about @sethah @yanboliang @jkbradley?
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@srowen I discuss some of these questions in the [blog
post](http://erikerlandson.github.io/blog/2016/05/26/measuring-decision-tree-split-quality-with-test-statistic-p-values/),
but the tl/dr
Github user srowen commented on the issue:
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I've not seen chi squared used as a split statistic; when is it
theoretically better than entropy? Or something a bit more fundamental like KL
divergence? It makes some sense but does require some
Github user HyukjinKwon commented on the issue:
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I don't have ML knowledge enough to review this. I can cc ML committer guys
who I can guess have some expertise from git blame but I hope there are some
sign-offs left here from some guys here
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@HyukjinKwon @thunterdb can you all take a look at this? It's been under
review for quite a long time!
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rebased to latest head of master
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@thunterdb can you take a look at this now that 2.2 is out?
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Ready for review
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@thunterdb this is ready for any further review
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@thunterdb patch is clean again. @HyukjinKwon found my problem.
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@thunterdb still can't diagnose what the source of this "fails to generate
doc" error is. I don't see anything wrong with the scaladoc.
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@thunterdb not sure what is failing in the CI.
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test this please
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@thunterdb apologize for the latency. I removed the default method defs
and rebased
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Github user wangmiao1981 commented on the issue:
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@thunterdb Can you take a look? Thanks!
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test this please
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Github user wangmiao1981 commented on the issue:
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@erikerlandson I am just helping clearing the stale PRs. :) I have no idea
whether they have intention to accept it.
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i stopped the build as i need to restart jenkins... i'll retrigger this
when we're back up and running.
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Hi @wangmiao1981,
I am still interested in this, but I don't have any sense about whether
upstream has any interest. Does upstream have any intention to accept it?
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@erikerlandson Are you still working on this PR? Thanks! Miao
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@holdenk @jkbradley looks like it's clean again
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test this please
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@holdenk yes, I'll rebase it this week.
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Is this something your still working on? If so it would be good to merge in
the latest master. We can also check with @jkbradley to see if he has some
review bandwidth.
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https://github.com/apache/spark/pull/13440
**[Test build #59751 has
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