[jira] [Created] (SPARK-17141) MinMaxScaler behaves weird when min and max have the same value and some values are NaN

["Alberto Bonsanto (JIRA)" <ji...@apache.org>]

Alberto Bonsanto created SPARK-17141:
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             Summary: 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: 2.0.0, 1.6.2
         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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