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new e44f308 [SPARK-26787] Fix standardizeLabels error message in
WeightedLeastSquares
e44f308 is described below
commit e44f308593e8cb02cdaeb5533f387c465aa60c6c
Author: bscan <brianjscann...@gmail.com>
AuthorDate: Thu Jan 31 19:50:18 2019 -0600
[SPARK-26787] Fix standardizeLabels error message in WeightedLeastSquares
Error message falsely states standardization=True is causing a problem,
even when standardization=False. The real issue is standardizeLabels=True,
which is set automatically in LinearRegression and not currently available in
the Public API.
## What changes were proposed in this pull request?
A simple change to an error message. More details here:
https://jira.apache.org/jira/browse/SPARK-26787
## How was this patch tested?
This does not change any functionality.
Closes #23705 from bscan/bscan-errormsg-1.
Authored-by: bscan <brianjscann...@gmail.com>
Signed-off-by: Sean Owen <sean.o...@databricks.com>
---
.../src/main/scala/org/apache/spark/ml/optim/WeightedLeastSquares.scala | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git
a/mllib/src/main/scala/org/apache/spark/ml/optim/WeightedLeastSquares.scala
b/mllib/src/main/scala/org/apache/spark/ml/optim/WeightedLeastSquares.scala
index 134d6a9..9f32603 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/optim/WeightedLeastSquares.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/optim/WeightedLeastSquares.scala
@@ -133,7 +133,7 @@ private[ml] class WeightedLeastSquares(
return new WeightedLeastSquaresModel(coefficients, intercept,
diagInvAtWA, Array(0D))
} else {
require(!(regParam > 0.0 && standardizeLabel), "The standard deviation
of the label is " +
- "zero. Model cannot be regularized with standardization=true")
+ "zero. Model cannot be regularized when labels are standardized.")
instr.logWarning(s"The standard deviation of the label is zero.
Consider setting " +
s"fitIntercept=true.")
}
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