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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