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Github user techaddict commented on the issue:
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@HyukjinKwon was busy, will restart this week.
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Github user HyukjinKwon commented on the issue:
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Hi @@techaddict, how is this PR going?
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Github user zhengruifeng commented on the issue:
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@techaddict @sethah I have some time to work on the porting, but I dont
find the umbrella JIRA
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Github user techaddict commented on the issue:
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@sethah I will revive this pr thanks ð
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Github user sethah commented on the issue:
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I think we decided to go a different direction than what is proposed here?
Actually, I still think there's merit in fixing the problem without having to
do full feature ports. Either way, I'm not
Github user zhengruifeng commented on the issue:
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the same TODO also appear in `HashingTF`, what about include it in this PR?
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Github user techaddict commented on the issue:
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@MLnick I will create a umbrella jira and start adding jira's for things
I'm aware of of and you can start prioritising ð sounds like a plan ?
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Github user MLnick commented on the issue:
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I'm also generally supportive of (1) - porting the code to `ml` and having
the `mllib` code wrap the `ml` version - this is the approach for other models
that have been done. Of course only once
Github user techaddict commented on the issue:
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@sethah @yanboliang I've started with migrating `IDF`, can you review the
WIP and if i'm going in the right direction
https://github.com/techaddict/spark/pull/2/files
there is some code
Github user yanboliang commented on the issue:
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@techaddict @sethah I'm more prefer option 1, since we would like to remove
spark.mllib package in a future release(may be 3.0) and we wouldn't like to
make any change to it except bug fix.
Github user techaddict commented on the issue:
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@sethah I agree, 2nd approach is much more reasonable.
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Github user sethah commented on the issue:
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I see this patch was created as a result of the PR that separated the
ml/mllib linalg packages, to avoid some inefficiencies in conversion. However,
it also is a partial step toward feature parity.
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cc: @dbtsai @mengxr
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