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

To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

Reply via email to