Package org.apache.spark.ml.feature

Class RobustScalerModel

Object
org.apache.spark.ml.PipelineStage
org.apache.spark.ml.Transformer
org.apache.spark.ml.Model<RobustScalerModel>
org.apache.spark.ml.feature.RobustScalerModel
All Implemented Interfaces:
Serializable, org.apache.spark.internal.Logging, RobustScalerParams, Params, HasInputCol, HasOutputCol, HasRelativeError, Identifiable, MLWritable
public class RobustScalerModel extends Model<RobustScalerModel> implements RobustScalerParams, MLWritable
Model fitted by RobustScaler.

param: range quantile range for each original column during fitting param: median median value for each original column during fitting

See Also:

  • Method Details

    • read

      public static MLReader<RobustScalerModel> read()

    • load

      public static RobustScalerModel load(String path)

    • lower

      public DoubleParam lower()
      Description copied from interface: RobustScalerParams
      Lower quantile to calculate quantile range, shared by all features Default: 0.25
      Specified by:
      lower in interface RobustScalerParams
      Returns:
      (undocumented)

    • upper

      public DoubleParam upper()
      Description copied from interface: RobustScalerParams
      Upper quantile to calculate quantile range, shared by all features Default: 0.75
      Specified by:
      upper in interface RobustScalerParams
      Returns:
      (undocumented)

    • withCentering

      public BooleanParam withCentering()
      Description copied from interface: RobustScalerParams
      Whether to center the data with median before scaling. It will build a dense output, so take care when applying to sparse input. Default: false
      Specified by:
      withCentering in interface RobustScalerParams
      Returns:
      (undocumented)

    • withScaling

      public BooleanParam withScaling()
      Description copied from interface: RobustScalerParams
      Whether to scale the data to quantile range. Default: true
      Specified by:
      withScaling in interface RobustScalerParams
      Returns:
      (undocumented)

    • relativeError

      public final DoubleParam relativeError()
      Description copied from interface: HasRelativeError
      Param for the relative target precision for the approximate quantile algorithm. Must be in the range [0, 1].
      Specified by:
      relativeError in interface HasRelativeError
      Returns:
      (undocumented)

    • outputCol

      public final Param<String> outputCol()
      Description copied from interface: HasOutputCol
      Param for output column name.
      Specified by:
      outputCol in interface HasOutputCol
      Returns:
      (undocumented)

    • inputCol

      public final Param<String> inputCol()
      Description copied from interface: HasInputCol
      Param for input column name.
      Specified by:
      inputCol in interface HasInputCol
      Returns:
      (undocumented)

    • uid

      public String uid()
      Description copied from interface: Identifiable
      An immutable unique ID for the object and its derivatives.
      Specified by:
      uid in interface Identifiable
      Returns:
      (undocumented)

    • range

      public Vector range()

    • median

      public Vector median()

    • setInputCol

      public RobustScalerModel setInputCol(String value)

    • setOutputCol

      public RobustScalerModel setOutputCol(String value)

    • transform

      public Dataset<Row> transform(Dataset<?> dataset)
      Description copied from class: Transformer
      Transforms the input dataset.
      Specified by:
      transform in class Transformer
      Parameters:
      dataset - (undocumented)
      Returns:
      (undocumented)

    • transformSchema

      public StructType transformSchema(StructType schema)
      Description copied from class: PipelineStage
      Check transform validity and derive the output schema from the input schema.

      We check validity for interactions between parameters during transformSchema and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by Param.validate().

      Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.

      Specified by:
      transformSchema in class PipelineStage
      Parameters:
      schema - (undocumented)
      Returns:
      (undocumented)

    • copy

      public RobustScalerModel copy(ParamMap extra)
      Description copied from interface: Params
      Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().
      Specified by:
      copy in interface Params
      Specified by:
      copy in class Model<RobustScalerModel>
      Parameters:
      extra - (undocumented)
      Returns:
      (undocumented)

    • write

      public MLWriter write()
      Description copied from interface: MLWritable
      Returns an MLWriter instance for this ML instance.
      Specified by:
      write in interface MLWritable
      Returns:
      (undocumented)

    • toString

      public String toString()
      Specified by:
      toString in interface Identifiable
      Overrides:
      toString in class Object