zhengruifeng commented on a change in pull request #31693:
URL: https://github.com/apache/spark/pull/31693#discussion_r589339808
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File path:
mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
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@@ -86,6 +87,21 @@ class LogisticRegressionSuite extends MLTest with
DefaultReadWriteTest {
df
}
+ binaryDatasetWithSmallVar = {
+ val nPoints = 10000
+ val coefficients = Array(-0.57997, 0.912083, -0.371077, -0.819866,
2.688191)
+ val xMean = Array(5.843, 3.057, 3.758, 1.199)
+ val xVariance = Array(0.6856, 0.1899, 3.116, 0.0001)
Review comment:
update xMean to 10.199;
if I update it to 100.199, then all labels sampled from
`generateMultinomialLogisticInput` are negative, that is to say, all label=0.
Can not train a model in R or MLLib.
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