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https://issues.apache.org/jira/browse/SPARK-9120?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14630644#comment-14630644
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Joseph K. Bradley commented on SPARK-9120:
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The prediction method is transform(). Model inherits from Transformer, which
declares transform(). The protected predict: Double method is really a
convenience for developers so they don't have to implement transform()
directly. But if you implement transform() yourself, you have complete control
over the schema of the input and output DataFrame. (Prediction will mean
adding one or more columns to the DataFrame.)
> Add multivariate regression (or prediction) interface
> -----------------------------------------------------
>
> Key: SPARK-9120
> URL: https://issues.apache.org/jira/browse/SPARK-9120
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 1.4.0
> Reporter: Alexander Ulanov
> Fix For: 1.4.0
>
> Original Estimate: 1h
> Remaining Estimate: 1h
>
> org.apache.spark.ml.regression.RegressionModel supports prediction only for a
> single variable with a method "predict:Double" by extending the Predictor.
> There is a need for multivariate prediction, at least for regression. I
> propose to modify "RegressionModel" interface similarly to how it is done in
> "ClassificationModel", which supports multiclass classification. It has
> "predict:Double" and "predictRaw:Vector". Analogously, "RegressionModel"
> should have something like "predictMultivariate:Vector".
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