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Dulaj Rajitha commented on SPARK-16993: --------------------------------------- When using the RandomForestRegressor. I trained using a dataframe with the label column and got a model. by: model = regressor.fit(trainData) But my test data does not have a label column. (Since this is the column I need to be prediicted). therefore when transforming I got a error. model.transform(test) > 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] -- 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