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https://issues.apache.org/jira/browse/SPARK-16993?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15415070#comment-15415070
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Sean Owen commented on SPARK-16993:
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You certainly need labels in your held out test set for evaluation. But you
seem to be talking about model.transform which is different. It is not clear
what you are describing.
> model.transform without label column in random forest regression
> ----------------------------------------------------------------
>
> Key: SPARK-16993
> URL: https://issues.apache.org/jira/browse/SPARK-16993
> Project: Spark
> Issue Type: Question
> Components: Java API, ML
> Reporter: Dulaj Rajitha
>
> I need to use a separate data set to prediction (Not as show in example's
> training data split).
> But those data do not have the label column. (Since these data are the data
> that needs to be predict the label).
> but model.transform is informing label column is missing.
> org.apache.spark.sql.AnalysisException: cannot resolve 'label' given input
> columns: [id,features,prediction]
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