[ https://issues.apache.org/jira/browse/SPARK-19947?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley resolved SPARK-19947. --------------------------------------- Resolution: Fixed Fix Version/s: 2.4.0 I'll mark this as complete. Those earlier PRs fixed some issues, and [SPARK-23562] should fix the rest. > RFormulaModel always throws Exception on transforming data with NULL or > Unseen labels > ------------------------------------------------------------------------------------- > > Key: SPARK-19947 > URL: https://issues.apache.org/jira/browse/SPARK-19947 > Project: Spark > Issue Type: Improvement > Components: ML > Affects Versions: 2.1.0 > Reporter: Andrey Yatsuk > Priority: Major > Fix For: 2.4.0 > > > I have trained ML model and big data table in parquet. I want add new column > to this table with predicted values. I can't lose any data, but can having > null values in it. > RFormulaModel.fit() method creates new StringIndexer with default > (handleInvalid="error") parameter. Also VectorAssembler on NULL values > throwing Exception. So I must call df.na.drop() to transform this DataFrame > and I don't want to do this. > Need add to RFormula new parameter like handleInvalid in StringIndexer. > Or add transform(Seq<Column>): Vector method which user can use as UDF method > in df.withColumn("predicted", functions.callUDF(rFormulaModel::transform, > Seq<Column>)) -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org