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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2017/08/22 23:59:01 UTC
[jira] [Commented] (SPARK-21681) MLOR do not work correctly when
featureStd contains zero
[ https://issues.apache.org/jira/browse/SPARK-21681?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16137638#comment-16137638 ]
Joseph K. Bradley commented on SPARK-21681:
-------------------------------------------
I'll leave this open until it's been backported to 2.2
> 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
> Fix For: 2.3.0
>
>
> 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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