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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2017/01/06 20:45:58 UTC
[jira] [Assigned] (SPARK-19110) DistributedLDAModel returns
different logPrior for original and loaded model
[ https://issues.apache.org/jira/browse/SPARK-19110?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-19110:
------------------------------------
Assignee: (was: Apache Spark)
> DistributedLDAModel returns different logPrior for original and loaded model
> ----------------------------------------------------------------------------
>
> Key: SPARK-19110
> URL: https://issues.apache.org/jira/browse/SPARK-19110
> Project: Spark
> Issue Type: Bug
> Components: ML, MLlib
> Reporter: Miao Wang
>
> While adding DistributedLDAModel training summary for SparkR, I found that the logPrior for original and loaded model is different.
> For example, in the test("read/write DistributedLDAModel"), I add the test:
> val logPrior = model.asInstanceOf[DistributedLDAModel].logPrior
> val logPrior2 = model2.asInstanceOf[DistributedLDAModel].logPrior
> assert(logPrior === logPrior2)
> The test fails:
> -4.394180878889078 did not equal -4.294290536919573
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