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https://issues.apache.org/jira/browse/SPARK-21681?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley updated SPARK-21681:
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Target Version/s: 2.2.1, 2.3.0
> MLOR do not work correctly when featureStd contains zero
> --------------------------------------------------------
>
> Key: SPARK-21681
> URL: https://issues.apache.org/jira/browse/SPARK-21681
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 2.2.0, 2.3.0
> Reporter: Weichen Xu
> Assignee: Weichen Xu
>
> MLOR do not work correctly when featureStd contains zero.
> We can reproduce the bug through such dataset (features including zero
> variance), will generate wrong result (all coefficients becomes 0)
> {code}
> val multinomialDatasetWithZeroVar = {
> val nPoints = 100
> val coefficients = Array(
> -0.57997, 0.912083, -0.371077,
> -0.16624, -0.84355, -0.048509)
> val xMean = Array(5.843, 3.0)
> val xVariance = Array(0.6856, 0.0) // including zero variance
> val testData = generateMultinomialLogisticInput(
> coefficients, xMean, xVariance, addIntercept = true, nPoints, seed)
> val df = sc.parallelize(testData, 4).toDF().withColumn("weight",
> lit(1.0))
> df.cache()
> df
> }
> {code}
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