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https://issues.apache.org/jira/browse/SPARK-17141?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15426988#comment-15426988
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Sean Owen commented on SPARK-17141:
-----------------------------------
Summarize the reproduction here? best to put it all here for the record.
If you have a small fix and can describe it then someone else can commit it,
though I think making a PR is a useful skill and not that hard. Worth taking a
shot at it.
> MinMaxScaler behaves weird when min and max have the same value and some
> values are NaN
> ---------------------------------------------------------------------------------------
>
> Key: SPARK-17141
> URL: https://issues.apache.org/jira/browse/SPARK-17141
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 1.6.2, 2.0.0
> Environment: Databrick's Community, Spark 2.0 + Scala 2.10
> Reporter: Alberto Bonsanto
> Priority: Trivial
>
> When you have a {{DataFrame}} with a column named {{features}}, which is a
> {{DenseVector}} and the *maximum* and *minimum* and some values are
> {{Double.NaN}} they get replaced by 0.5, and they should remain with the same
> value, I believe.
> I know how to fix it, but I haven't ever made a pull request. You can check
> the bug in this
> [notebook|https://databricks-prod-cloudfront.cloud.databricks.com/public/4027ec902e239c93eaaa8714f173bcfc/2485090270202665/3126465289264547/8589256059752547/latest.html]
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