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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} -- This message was sent by Atlassian JIRA (v6.4.14#64029) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org