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Alexander Ulanov commented on SPARK-9120: ----------------------------------------- I think it should work for the train (aka fit) that has to return the model, not sure about the model itself. The common ancestor Model does not contain anything that can be called for prediction, its direct successor PredictionModel has predict:Double. Is there another way that you were mentioning? > 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". -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org