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https://issues.apache.org/jira/browse/SPARK-11439?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14993281#comment-14993281
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Nakul Jindal commented on SPARK-11439:
--------------------------------------
[info] - linear regression model training summary *** FAILED *** (966
milliseconds)
[info] Expected 0.009955579236410212 and 0.00972035 to be within 1.0E-5 using
relative tolerance. (TestingUtils.scala:78)
[info] org.scalatest.exceptions.TestFailedException:
[info] at
org.apache.spark.mllib.util.TestingUtils$DoubleWithAlmostEquals.$tilde$eq$eq(TestingUtils.scala:78)
[info] at
org.apache.spark.ml.regression.LinearRegressionSuite$$anonfun$11$$anonfun$apply$mcV$sp$9.apply(LinearRegressionSuite.scala:606)
[info] at
org.apache.spark.ml.regression.LinearRegressionSuite$$anonfun$11$$anonfun$apply$mcV$sp$9.apply(LinearRegressionSuite.scala:559)
.....
> Optimization of creating sparse feature without dense one
> ---------------------------------------------------------
>
> Key: SPARK-11439
> URL: https://issues.apache.org/jira/browse/SPARK-11439
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: Kai Sasaki
> Priority: Minor
>
> Currently, sparse feature generated in {{LinearDataGenerator}} needs to
> create dense vectors once. It is cost efficient to prevent from generating
> dense feature when creating sparse features.
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