Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@yanboliang @sethah
Any suggestion on moving this PR forward? Appreciate your comments and
reviews.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17590
The change is fine to me. With this, we can define function/argument names
using multiple styles such as `as.json.array`, `as_json_array`, `asJsonArray`.
Is there a preferred style among
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/17571#discussion_r110457676
--- Diff: examples/src/main/r/ml/glm.R ---
@@ -44,8 +44,9 @@ gaussianGLM2 <- glm(label ~ features, gaussianDF, family
= "gaussian")
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/17571#discussion_r110457466
--- Diff: examples/src/main/r/ml/glm.R ---
@@ -44,8 +44,9 @@ gaussianGLM2 <- glm(label ~ features, gaussianDF, family
= "gaussian")
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17571
@felixcheung
Just noticed that the current example for logistic regression in the
programming guide did not seem to be a good one. It did not converge using
IRWLS, and Quasi-Newton
GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/17571
[SPARK-20258][Doc][SparkR] Fix SparkR logistic regression example in
programming guide (did not converge)
## What changes were proposed in this pull request?
SparkR logistic
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17553
Issues fixed. Thanks.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17553
@felixcheung
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GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/17553
[SPARK-20026][Doc] Add Tweedie example for SparkR in programming guide
## What changes were proposed in this pull request?
Add Tweedie example for SparkR in programming guide.
The doc
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17084
Thanks for the PR. I think this is helpful. Will take a look next week.
Quite swamped recently.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
@felixcheung Could you merge this please? Thanks!
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
Sorry that I forgot to address that comment. Fixed now.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
@felixcheung Thanks for the feedback. Made a new commit that
1. change `variancePower` and `linkPower` to `var.power` and `link.power`.
2. use `link = NULL` for tweedie family
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16729#discussion_r105576051
--- Diff: R/pkg/R/mllib_regression.R ---
@@ -100,6 +120,12 @@ setMethod("spark.glm", signature(data =
"SparkDataFrame"
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
One other change I could make is to change `variancePower` and `linkPower`
to `var.power` and `link.power` to be consistent with `statmod`. But l would
like to get your feedback on this new
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
@felixcheung OK, new implementation of # 3. Now works in two ways:
1. `family = "tweedie"` + `variancePower` + `linkPower`
2. When `statmod` is available, `tweedie()`
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
@felixcheung If we go with # 3, do we still want to compatibility with
statmod::tweedie? It's confusing to have two different ways of specifying the
same model.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
@felixcheung Could you take a look at this new fix when you get a chance?
Thanks.
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Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/17146#discussion_r104853968
--- Diff: python/pyspark/ml/tests.py ---
@@ -1223,6 +1223,26 @@ def test_apply_binary_term_freqs(self
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17146
This looks good to me. Thanks
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17146
Will take a look tonight.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
@felixcheung Yes, the SparkR `tweedie` is not exported. See below.
```
model1 <- spark.glm(training, Sepal_Width ~ Sepal_Length + Species,
+ fam
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
@felixcheung Sorry for taking so long for this update.
I think your first suggestion makes most sense, i.e., we do not expose the
internal `tweedie`.
When `statmod` is loaded
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/17159#discussion_r104335939
--- Diff: R/pkg/R/DataFrame.R ---
@@ -2685,7 +2686,8 @@ setMethod("unionAll",
#' Union two or more SparkDataFrames
#'
-#'
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17159
Makes sense. Made changes to rbind and added tests. Please take a look.
Thanks.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17159
@felixcheung OK, did not know it was by design. It does seem that the
`union` behavior is similar to R's SQL (in `sqldf`), but as you pointed out,
the overload method `rbind` is different
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17161
I think most examples in R packages are (supposed to be) runnable. Coming
from a user perspective, I find it useful if I can run the examples directly
and see what the function does in action
GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/17161
[SPARK-19819][SparkR] Use concrete data in SparkR DataFrame examples
## What changes were proposed in this pull request?
Many examples in SparkDataFrame methods uses:
```
path
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17159
The current implementation accepts data frames with different schemas. See
issues below:
```
df <- createDataFrame(data.frame(name = c("Michael", "Andy", "
GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/17159
[SPARK-19818][SparkR] union should check for name consistency of input data
frames
## What changes were proposed in this pull request?
Added checks for name consistency of input data
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17115
@srowen @felixcheung
Thanks for the clarification. I will open another PR to add real data
examples for the SparkDataFrame methods.
I have seen lots of R package document
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17115
@HyukjinKwon Thanks. Updated title.
@felixcheung Updated doc and added tests. Thanks!
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17115
@felixcheung I see lots of the SparkDataFrame methods use the following in
examples:
```
path <- "path/to/file.json"
df <- read.json(path)
```
I'
GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/17115
[Doc][Minor] Update R doc
Update R doc:
1. columns, names and colnames returns a vector of strings, not **list** as
in current doc.
2. `colnames<-` does allow the subset assignm
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17105
@felixcheung Thanks for the clarification. I will close this then.
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Github user actuaryzhang closed the pull request at:
https://github.com/apache/spark/pull/17105
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17105
@felixcheung Ahh, it seems that we have some conflicting design issues.
1. From the test in collect() and crossJoin, it seems to allow dup names in
SparkDataFrame by design
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17105
@felixcheung
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GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/17105
[SPARK-19773][SparkR] SparkDataFrame should not allow duplicate names
## What changes were proposed in this pull request?
SparkDataFrame in SparkR seems to accept duplicate names
GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/17103
[Minor][Doc] Update GLM doc to include tweedie distribution
Update GLM documentation to include the Tweedie distribution. #16344
@jkbradley @yanboliang
You can merge this pull
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r103004564
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -1152,4 +1173,33 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r103003591
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/r/GeneralizedLinearRegressionWrapper.scala
---
@@ -99,37 +95,23 @@ private[r] object
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r103003515
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -34,6 +35,7 @@ import org.apache.spark.rdd.RDD
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/17017#discussion_r102648326
--- Diff: R/pkg/R/DataFrame.R ---
@@ -1776,6 +1780,10 @@ setMethod("[[", signature(x = "SparkDataFrame", i =
"numericOrc
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17017
@felixcheung
Simple example to illustrate this
```
df <- suppressWarnings(createDataFrame(iris))
df[[1:2]]
```
Instead of issuing warning and taking the first elem
GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/17017
[SPARK-19682][SparkR] Issue warning (or error) when subset method "[["
takes vector index
## What changes were proposed in this pull request?
The `[[` method is supposed to tak
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17005
@HyukjinKwon Thanks. I'll try retesting this.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17005
Cannot figure out what's exactly causing the test to fail. Error message is
not informative. Any help please?
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/17005
@srowen @jkbradley @felixcheung @sethah @yanboliang
One question is: is it better to move the `HasStringOrderType` trait to the
shared params? This is only used by StringIndexer
GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/17005
[SPARK-14659][ML] RFormula supports setting base level both by frequency
and alphabetically
## What changes were proposed in this pull request?
Current RFormula drops the least frequent
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@sethah Is there anything else you would recommend for this PR? Thanks.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16630
@felixcheung Could you take another look at this PR? Thanks.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16630
@imatiach-msft I'm not sure the R^2s are used much in the GLM context. The
deviance, loglikelihood and AIC/BICs are most often used for ANOVA and model
comparison. The GLM
[book](https
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16630
@imatiach-msft @felixcheung
I cleaned up the tests as suggested, and also updated the R GLM wrapper to
use the result from this PR. Please let me know if there is any other
suggestions
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r101822942
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
---
@@ -1104,6 +1103,83 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r101822971
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
---
@@ -1104,6 +1103,83 @@ class
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16729
@felixcheung Thanks for the discussions. Will work on this in two weeks.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16630
@felixcheung @imatiach-msft Thanks much for the review. Made most changes
suggested. Please see my inline replies.
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Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r101160217
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -1152,4 +1170,32 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r101160069
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -915,6 +917,22 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r101159255
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
---
@@ -1104,6 +1103,83 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r101159105
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -915,6 +917,22 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r101159146
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -1152,4 +1170,32 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r101158825
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -1152,4 +1170,32 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16630#discussion_r101158362
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -915,6 +917,22 @@ class
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@sethah Thanks much for your review. I've made a new commit that addressed
all your comments. Please see my inline comments. Let me know if there is any
other suggestions. Thanks
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r100976816
--- 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 a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r100976709
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -1139,54 +1189,52 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r100975590
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -944,15 +981,27 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r100975556
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -406,6 +435,14 @@ object
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r100975164
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -168,6 +179,7 @@ private[regression] trait
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r100974912
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
---
@@ -798,77 +798,160 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r100974891
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
---
@@ -798,77 +798,160 @@ class
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@sethah The predict method can work with new data in R. See below. Shall we
focus on the current implementation, instead of discussing the details of the R
behavior? :)
Let me know
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@sethah Thanks much for your review.
Regarding prediction, both R and my implementation here allow prediction
with offsets. If the users want to get the predicted rates (instead
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r100581520
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -1218,16 +1266,35 @@ class
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@sethah Yes, that is lots of work. However, the only critical change (since
the last commit) is on the calculation of the null deviance. The other changes
are mainly because of updating
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16699
@sethah @imatiach-msft
Please review the new commit. Main changes:
- Fix issue in null deviance calculation in the presence of offset. Except
for special cases (Gaussian
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16630
Could somebody help review this PR? I think this will make gathering the
estimation results in Scala much easier. This will also be helpful in
constructing the tests. For example, the GLM
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
@jkbradley Thanks much for the review and suggestion. I updated the error
message. Please let me know if there's 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
Can one of the admins merge this PR since we have two approvals now?
Thanks.
@srowen @jkbradley @felixcheung @yanboliang
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
@sethah Thanks for the comments.
OK, added more tests to cover all families. It's not possible to test all
family and link combination if that's what you mean: the tweedie family
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
@sethah @imatiach-msft Could you take another look and let me know if there
are any additional changes needed on this PR? Thanks!
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16794
@felixcheung I'll be happy to look into this and fix it. Do you want me to
open a new JIRA or just create a PR against SPARK-19460?
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16794
@felixcheung I am in favor of the first proposal to support dot in names.
I'm curious why this was not supported yet since we can create DataFrame in
Spark with dot in names?
```
val
GitHub user actuaryzhang reopened a pull request:
https://github.com/apache/spark/pull/16794
[SPARK-19452][SparkR] Fix bug in the name assignment method
## What changes were proposed in this pull request?
The names method fails to check for validity of the assignment values
Github user actuaryzhang closed the pull request at:
https://github.com/apache/spark/pull/16794
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Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16740#discussion_r99460883
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquares.scala
---
@@ -89,7 +89,7 @@ private[ml] class
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
@sethah Thanks for the review. Made changes you suggested (except for the
nit part). I added more tests although I don't think they are really necessary.
The analytical approach is taking
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16794
@felixcheung @wangmiao1981
I spent quite some time on this b/c I could not replicate the results and
all tests on my end worked.
Then I updated my local spark with a pull request
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16799
Errors can be seen in #16794.
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GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/16799
[SparkR] fix error in vignettes
## What changes were proposed in this pull request?
Current version has error in vignettes:
```
model <- spark.bisectingKmeans(df, Sepal_Len
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16794
jenkins, retest this please
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16794
Not sure why the unit test on kmeans summary failed since nothing was
changed there. Also, all unit tests passed on my computer.
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Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16794
An example illustrating the issue:
```
df <- suppressWarnings(createDataFrame(iris))
# this is error
colnames(df) <- NULL
# this should report error
na
GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/16794
[SPARK-19452][SparkR] Fix bug in the name assignment method
## What changes were proposed in this pull request?
The names method fails to check for validity of the assignment values
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16699#discussion_r99406022
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
---
@@ -743,6 +743,84 @@ class
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/16740
@seth @imatiach-msft Let me know if there is any other changes needed.
Thanks much for your review!
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Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16740#discussion_r99277921
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
---
@@ -743,6 +744,48 @@ class
Github user actuaryzhang commented on a diff in the pull request:
https://github.com/apache/spark/pull/16740#discussion_r99276315
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
---
@@ -335,6 +335,11 @@ class
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