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https://issues.apache.org/jira/browse/SPARK-11534?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sandeep Pal updated SPARK-11534:
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Description:
According to the definition of uniformVectorRDD, it is supposed to generate the
uniformly distributed data with mean ~0.0 and standard deviation ~1.
[Definition: Generates an RDD comprised of i.i.d. samples from the uniform
distribution U(0.0, 1.0).]
But it is generating the data with mean ~0.5 and sd of ~0.28.
PS: uniformRDD is working correctly as per description with uniform
distribution U(0.0, 1.0) and uniformVectorRDD should be generating data with
same distribution.
was:
According to the definition of uniformVectorRDD, it is supposed to generate the
uniformly distributed data with mean ~0.0 and standard deviation ~1.
[Definition: Generates an RDD comprised of i.i.d. samples from the uniform
distribution U(0.0, 1.0).]
But it is generating the data with mean ~0.5 and sd of ~0.28.
PS: uniformRDD is working correctly as per description with uniform
distribution U(0.0, 1.0) .
> MLLib uniformVectorRDD wrong data generation
> --------------------------------------------
>
> Key: SPARK-11534
> URL: https://issues.apache.org/jira/browse/SPARK-11534
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Affects Versions: 1.5.1
> Environment: Spark 1.6.0-SNAPSHOT standalone on centos 6.6
> Single node VM machine, 8 cores 16 GB memory
> Reporter: Sandeep Pal
> Labels: mllib
>
> According to the definition of uniformVectorRDD, it is supposed to generate
> the uniformly distributed data with mean ~0.0 and standard deviation ~1.
> [Definition: Generates an RDD comprised of i.i.d. samples from the uniform
> distribution U(0.0, 1.0).]
> But it is generating the data with mean ~0.5 and sd of ~0.28.
> PS: uniformRDD is working correctly as per description with uniform
> distribution U(0.0, 1.0) and uniformVectorRDD should be generating data with
> same distribution.
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