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Posted to reviews@spark.apache.org by tanwanirahul <gi...@git.apache.org> on 2016/02/16 15:54:57 UTC
[GitHub] spark pull request: [MINOR][MLLIB] Public visibility for eval metr...
GitHub user tanwanirahul opened a pull request:
https://github.com/apache/spark/pull/11219
[MINOR][MLLIB] Public visibility for eval metric's dataframe constructor
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/tanwanirahul/spark metrics_constructor
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/11219.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #11219
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commit a7d8af9f904d7a5d07fe90899379d8ff555e1d8a
Author: Rahul Tanwani <ra...@rahuls-macbook-pro.local>
Date: 2016-02-16T14:54:16Z
[MINOR][MLLIB] Public visibility for eval metric's dataframe constructor
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[GitHub] spark pull request: [MINOR][MLLIB] Public visibility for eval metr...
Posted by tanwanirahul <gi...@git.apache.org>.
Github user tanwanirahul commented on the pull request:
https://github.com/apache/spark/pull/11219#issuecomment-184815144
@JoshRosen Sure. If someone confirms on this, I will add that.
On if we need it: The pipeline apis work on the dataframes. If we don't have this interface, we are required to convert dataframes back to RDD and make it work.
The other question I had was: Current implementation assumes the first column to be prediction and the second one the label/observation. Is this reasonable assumption to make? Shouldn't we rather expect the prediction and label/observation column names to be provided, the way other ml algorithms expect?
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[GitHub] spark pull request: [MINOR][MLLIB] Public visibility for eval metr...
Posted by HyukjinKwon <gi...@git.apache.org>.
Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/11219#issuecomment-213243550
@tanwanirahul Could you fill up the PR description with the purpose please?
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[GitHub] spark pull request: [MINOR][MLLIB] Public visibility for eval metr...
Posted by JoshRosen <gi...@git.apache.org>.
Github user JoshRosen commented on the pull request:
https://github.com/apache/spark/pull/11219#issuecomment-184754414
Not sure whether this should be public or not (I don't know much about MLlib), but shouldn't this have an `@Since(2.0.0)` annotation if it's going to be public?
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[GitHub] spark pull request: [MINOR][MLLIB] Public visibility for eval metr...
Posted by jkbradley <gi...@git.apache.org>.
Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/11219#issuecomment-205975994
I don't think this should be public. If this is needed for the DataFrame-based API, then we should discuss providing the evaluation metric classes within the spark.ml package. Could you please close this PR, and we can discuss more on JIRA? Thanks.
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[GitHub] spark pull request: [MINOR][MLLIB] Public visibility for eval metr...
Posted by tanwanirahul <gi...@git.apache.org>.
Github user tanwanirahul commented on the pull request:
https://github.com/apache/spark/pull/11219#issuecomment-213249792
@jkbradley Make sense. Thanks.
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[GitHub] spark pull request: [MINOR][MLLIB] Public visibility for eval metr...
Posted by tanwanirahul <gi...@git.apache.org>.
Github user tanwanirahul closed the pull request at:
https://github.com/apache/spark/pull/11219
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[GitHub] spark pull request: [MINOR][MLLIB] Public visibility for eval metr...
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/11219#issuecomment-184715149
Can one of the admins verify this patch?
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[GitHub] spark pull request: [MINOR][MLLIB] Public visibility for eval metr...
Posted by tanwanirahul <gi...@git.apache.org>.
Github user tanwanirahul commented on the pull request:
https://github.com/apache/spark/pull/11219#issuecomment-185604502
@mengxr - I see you have added this code. Could you please check if this change would be good to have. If not, I will happily close.
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