[GitHub] [spark] WeichenXu123 commented on a change in pull request #31693: [SPARK-34448][ML] Binary logistic regression incorrectly computes the intercept and coefficients with small var features

[GitBox <gi...@apache.org>]

WeichenXu123 commented on a change in pull request #31693:
URL: https://github.com/apache/spark/pull/31693#discussion_r589311302



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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:
       Why not increase the xMean to a big value like 100 for the feature with var=0.0001
    ? 




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