stringindexingwrapper

Type Members

1. class FilterNotTransformer extends sparkutils.ML.Transformer with MLWritable

   

   Transformer that filters out columns specified in columnsToOmit.

2. class RenameColumnTransformer extends sparkutils.ML.Transformer with MLWritable with Params

   

   Transformer that changes column name.

3. class SetUpPredictionColumnTransformer extends sparkutils.ML.Transformer with MLWritable

   

   Transformer that filters out prediction column and renames predictedLabels column to prediction column.

4. abstract class StringIndexingEstimatorWrapper[M <: org.apache.spark.ml.Model[M], E <: org.apache.spark.ml.Estimator[M], MW <: SparkModelWrapper[M, E], SIWP <: StringIndexingWrapperModel[M, E]] extends Estimator[SIWP] with ParamsWithSparkWrappers

   

   Some spark operation assume their input was string-indexed.

   Some spark operation assume their input was string-indexed. User-experience suffers from this requirement. We can work around it by wrapping estimation in StringIndexerEstimatorWrapper. StringIndexerEstimatorWrapper plugs in StringIndexer before operation. It also makes it transparent for clients' components by reverting string indexing with labelConverter.

5. abstract class StringIndexingWrapperModel[M <: org.apache.spark.ml.Model[M], E <: org.apache.spark.ml.Estimator[M]] extends Transformer

   

   Model wrapper adding 'string indexing' behaviour.

   Model wrapper adding 'string indexing' behaviour.

   Concrete models (like GBTClassificationModel) must be concrete classes (leaves in hierarchy). That's why this class must be abstract.