Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16740#discussion_r99269006
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
---
@@ -743,6 +743,55 @@ class
Github user actuaryzhang commented on the issue:
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@srowen would you please take a look and merge this if all is good? Thanks.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
@sethah Your formula for offset does not seem to be a general solution, and
I'm not sure if there exists an analytical formula, in particular when the link
function is not identity or log
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
@felixcheung The one from statmod will be masked and must be called using
`statmod:tweedie`.
We can copy the whole `tweedie` function from statmod into `SparkR` and
this will avoid
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
@felixcheung Great point! Yes, I think it's better to stick with the
statmod syntax and allow the tweedie family to be specified
as`tweedie(var.power, link.power)`. I tried a few ways to allow
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
@sethah Thanks for the clarification and providing an implementation. So,
the pros is some speed improvement and the cons is the increased complexity
(now we have three case: one for intercept
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
@sethah Thanks for your input. I can add more tests, but they are not
adding too much since the algorithm is already tested in other tests.
The analytical approach does not integrate
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
@sethah Yes, we can directly compute the intercept easily. But I'm
concerned that such special handling may not integrate well with other features
or future changes. For example, we will need
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
@sethah Thanks for your review. Yes, using `foldLeft` would be the simplest
fix. I have included both your suggested changes in the new commit.
Yes, we could handle the special case
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r98580805
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -336,14 +361,19 @@ class
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@yanboliang @zhengruifeng @srowen
Could you guys take a look and let me know if there is any changes needed?
Thanks much!
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@imatiach-msft Thanks much for your review. Renamed `off`.
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Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r98496017
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -336,14 +361,19 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16740#discussion_r98493237
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquares.scala
---
@@ -86,13 +86,11 @@ private[ml] class
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
@imatiach-msft Thanks for the comments! This test is based on existing
tests in GLM. I can try to improve the style and streamline **all** tests in
another PR but it will be weird to just
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
@srowen Thanks much for the suggestion. Included the simplification. Please
let me know if there is anything else needed for this PR. Thanks!
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
The following is a simple example to illustrate the issue.
```
val dataset = Seq(
(1.0, 1.0, 2.0, 0.0, 5.0),
(0.5, 2.0, 1.0, 1.0, 2.0
GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/16740
[SPARK-19400] Allow GLM to handle intercept only model
## What changes were proposed in this pull request?
Intercept-only GLM is failing for non-Gaussian family because of reducing
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16729#discussion_r98363560
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/r/GeneralizedLinearRegressionWrapper.scala
---
@@ -143,7 +150,12 @@ private[r] object
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16729#discussion_r98363550
--- Diff: R/pkg/inst/tests/testthat/test_mllib_regression.R ---
@@ -77,6 +77,18 @@ test_that("spark.glm and predict", {
out <- c
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
@felixcheung Thanks so much for your quick and detailed review. I have made
a new commit that removed dependency on `statmod` and fixed the issues you
pointed out. The major change is to add
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16730
@felixcheung I created a JIRA ticket and added in some tests. Please take a
look. Thanks.
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GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/16730
[Minor][SparkR]Convert coefficients in summary to matrix
## What changes were proposed in this pull request?
The `coefficients` component in model summary should be 'matrix
GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/16729
[SPARK-19391][SparkR][ML] Tweedie GLM API for SparkR
## What changes were proposed in this pull request?
Port Tweedie GLM #16344 to SparkR
@felixcheung @yanboliang
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@zhengruifeng Thanks for the suggestions. Added casting and
instrumentation.
@imatiach-msft Thanks for the clarification! It is probably worth another
PR to clean up all tests in GLM
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r98077231
--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/Instance.scala
---
@@ -27,3 +27,25 @@ import org.apache.spark.ml.linalg.Vector
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@imatiach-msft Many thanks again for the review. I have incorporated some
of your suggestions:
1. Create initialization of instance directly if it is Gaussian(identity)
to avoid expensive
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@imatiach-msft Thanks so much for your detailed review. Incredibly helpful.
I've addressed all your comments in the new commit. Major changes are
highlighted below:
1. Create
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@zhengruifeng @imatiach-msft
Thanks much for pointing out the issue due to the hasOffset trait. This is
what caused the test to fail. I have moved it to the GLRBase class. Things
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16630
This test just resists to start. Could someone help? Many thanks!
@srowen @jkbradley @MLnick @yanboliang
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Github user actuaryzhang commented on the issue:
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jenkins, retest this please
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GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/16699
[SPARK-18710] Add offset in GLM
## What changes were proposed in this pull request?
Add support for offset in GLM. This is useful for at least two reasons:
1. Account for exposure
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16630
jenkins, test this please
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16675
@yanboliang Thanks. Seems to have passed tests.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@yanboliang Thanks so much for your detailed review. Your suggestions make
lots of sense and I have included all of them in the new commit. Let me know if
there is any other change needed
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16675
@yanboliang Thanks for the quick response. How about the new commit, where
I just change the value from `getFamily` to lower case when necessary, i.e., in
the calculation of p-value
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16675
I would prefer that `getFamily` returns lower case values directly, because
using `getFamily.toLowerCase` can get very cumbersome and I use this a lot in
another PR #16344. If we want to keep
GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/16675
[SPARK-19155][ML] make getFamily case insensitive
## What changes were proposed in this pull request?
This is a supplement to PR #16516 which did not make the value from
`getFamily` case
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16630
jenkins test this please
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
Could anybody help me understand what's causing this test to fail? I see
several other ML PR failing as well, with the same error message like below:
> Error instrument
Github user actuaryzhang commented on the issue:
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@srowen @yanboliang @felixcheung @jkbradley Could you help kick off the new
test please? Thanks.
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Github user actuaryzhang commented on the issue:
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@srowen @yanboliang @felixcheung Could you help kick off the new test
please? Seems to be hanging for a day now. Thanks much.
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Github user actuaryzhang commented on the issue:
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16630
The following code illustrates the idea of this PR.
```
val datasetWithWeight = Seq(
(1.0, 1.0, 0.0, 5.0),
(0.5, 2.0, 1.0, 2.0),
(1.0, 3.0, 2.0, 1.0
GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/16630
[SPARK-19270][ML] Add summary table to GLM summary
## What changes were proposed in this pull request?
Add R-like summary table to GLM summary, which includes feature name (if
exist
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@yanboliang Finally, the test is done. Is there anything else needed for
this PR?
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
Jenkins, retest this please
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
Still not testing... Been in the status "Asked to test" for a few days now.
How can we resolve this? Please help kick off the test. Thanks!
@yanboliang @felixcheung @sr
Github user actuaryzhang commented on the issue:
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Jenkins, retest this please
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Github user actuaryzhang commented on the issue:
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Jenkins, test this please.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@yanboliang Thanks for the review and comments. I have made a new commit
that addressed all your comments. The main change is the new companion object
`FamilyAndLink` and factory methods
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r96061883
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -242,9 +316,9 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r96061873
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -613,25 +758,67 @@ object
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@yanboliang Thanks. Look forward to your feedback.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
Sorry about closing this prematurely. I'm giving it another shot and I
think I have an elegant solution to include `linkPower`. The new commit adds
the following:
1. It implements
Github user actuaryzhang commented on the issue:
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GitHub user actuaryzhang reopened a pull request:
https://github.com/apache/spark/pull/16344
[SPARK-18929][ML] Add Tweedie distribution in GLM
## What changes were proposed in this pull request?
I propose to add the full Tweedie family into the
GeneralizedLinearRegression model
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@srowen @yanboliang
I'm closing this PR since it does not seem to be very clean to integrate
into the current GLM setup. I appreciate all the comments and discussions.
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Github user actuaryzhang closed the pull request at:
https://github.com/apache/spark/pull/16344
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@yanboliang Thanks for the feedback. However, I'm not sure why we need to
be consistent with R on this one. The usage of 'tweedie' glm almost always uses
`link.power = 0, 1, -1
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r94849556
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -397,32 +432,121 @@ object
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r94849540
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -365,7 +401,6 @@ object
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r94849501
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -158,6 +183,16 @@ class
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@yanboliang Thanks for the detailed review. I have made all changes you
suggested except for the part on the new power link function. Yes, the
canonical link in the Tweedie in general is `1.0
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@yanboliang Did you get a chance to take another look at this? Thanks.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@srowen Made a new commit according to your suggestion. Everything looking
good now?
@yanboliang
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Github user actuaryzhang commented on the issue:
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@srowen @yanboliang
Any additional issues regarding this PR?
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@yanboliang Thanks much for the detailed comments. I have addressed all of
them in the new commits. Please take another look.
@srowen
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Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r93672741
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -303,20 +337,24 @@ object
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@srowen Thanks for the comments. Makes lots of sense to move the switch to
subclass. I did not know one could override a `val`.
In the new commit, I have moved the `defaultLink
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@srowen @yanboliang Thanks much for the feedback. I now have a better
understanding of the code and the issue. I have made new commits reflecting
your suggestions. The major changes
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r93565567
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -303,14 +341,15 @@ object
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r93565335
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -64,6 +64,27 @@ private[regression] trait
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r93486159
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -303,14 +341,15 @@ object
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r93482978
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -242,7 +275,12 @@ class
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
@srowen Thanks for the comments. Really helpful. I have made a new commit
that addresses the issues you raised:
- I think the use of a global family object does not work well
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r93290858
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -592,6 +629,59 @@ object
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16344#discussion_r93289668
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -592,6 +629,59 @@ object
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16344
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GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/16344
[SPARK-18929][ML] Add Tweedie distribution in GLM
## What changes were proposed in this pull request?
I propose to add the full Tweedie family into the
GeneralizedLinearRegression model
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16149
@srowen @sethah
Thanks for all the helpful discussions!
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16149
@srowen @sethah
One more commit that adds a test case with `weight = 4.7` which will round
up to 5 to test the case @sethah described. All tests passed. I'm pretty sure
R's rounding
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16149
@sethah Would you please review this? Thanks.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16149
@sethah @srowen
I updated the documentation. I think we have everything needed for this
fix. Please merge and close this PR if there is no other issue. Thanks much for
all the comments
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16149#discussion_r91643659
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -468,11 +469,7 @@ object
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16149#discussion_r91643515
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
---
@@ -715,7 +715,7 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16149#discussion_r91563322
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
---
@@ -715,7 +715,7 @@ class
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16149
@sethah @srowen I have added a comment to the weigthCol doc for the
Binomial case.
I also updated to test the case `weight < 0.5`, i.e., `round(weight) = 0`.
All tests pas
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16149#discussion_r91440862
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -479,7 +485,12 @@ object
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16149
@srowen @sethah
I have cleaned up the change as suggested. Please review and let me know if
there is any question.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16149
@srowen @sethah
Thanks for the comments. Yes, the major use case is to be able to handle
multiple trials (integer weight, real-valued response). Indeed, a better way to
do this is through
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16149#discussion_r91246870
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -479,7 +479,12 @@ object
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16131
@srowen Is this ready to be merged?
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16131
@srowen Done. Thanks for the suggestion.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16131
@sethah Thanks for the review. I have updated according to your suggestion.
@yanboliang @srowen Please take another look. Thanks.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16131
@srowen @yanboliang
I have updated the code and further cleaned up the test. Please review and
let me know if there is any question. Thanks.
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Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16131#discussion_r90965352
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
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@@ -505,7 +505,7 @@ object
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16131#discussion_r90955908
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -505,7 +505,7 @@ object
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16149
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