Github user feynmanliang commented on the pull request:
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@dbtsai validating coefficients with R will be harder than expected,
`glmnet` requires feature dimension >= 2 and `glm` doesn't yield +/- Infinity
intercepts when
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Github user asfgit closed the pull request at:
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Github user dbtsai commented on the pull request:
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Merged into master. Thanks.
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Github user dbtsai commented on the pull request:
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A followup PR is created: https://issues.apache.org/jira/browse/SPARK-12908
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Github user dbtsai commented on the pull request:
https://github.com/apache/spark/pull/10743#issuecomment-172954097
Ideally, we would like to see the one without intercept to ensure that
nothing will not be messed up during the refactoring. I'll merge now, and let's
add the test for
Github user feynmanliang commented on a diff in the pull request:
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--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
---
@@ -276,113 +276,123 @@ class LogisticRegression
Github user feynmanliang commented on a diff in the pull request:
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--- Diff:
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@@ -276,113 +276,123 @@ class LogisticRegression
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Github user feynmanliang commented on the pull request:
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@dbtsai Added `fitIntercept=false` tests and fixed comments/`logWarning`
messages.
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Github user dbtsai commented on a diff in the pull request:
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Github user dbtsai commented on the pull request:
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LGTM except couple minor issues. Thanks.
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Github user feynmanliang commented on the pull request:
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@dbtsai @jkbradley ready for second review.
The big diff is because I grouped the same label cases with the normal case
to generate `coefficients`,
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[SPARK-12804][ML] Fix LogisticRegression with FitIntercept on all same
label training data
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Github user dbtsai commented on a diff in the pull request:
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