Package org.apache.spark.ml.feature

Class ImputerModel

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

param: surrogateDF a DataFrame containing inputCols and their corresponding surrogates, which are used to replace the missing values in the input DataFrame.

See Also:

  • Method Details

    • read

      public static MLReader<ImputerModel> read()

    • load

      public static ImputerModel load(String path)

    • strategy

      public final Param<String> strategy()
      Description copied from interface: ImputerParams
      The imputation strategy. Currently only "mean" and "median" are supported. If "mean", then replace missing values using the mean value of the feature. If "median", then replace missing values using the approximate median value of the feature. If "mode", then replace missing using the most frequent value of the feature. Default: mean

      Specified by:
      strategy in interface ImputerParams
      Returns:
      (undocumented)

    • missingValue

      public final DoubleParam missingValue()
      Description copied from interface: ImputerParams
      The placeholder for the missing values. All occurrences of missingValue will be imputed. Note that null values are always treated as missing. Default: Double.NaN

      Specified by:
      missingValue in interface ImputerParams
      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)

    • outputCols

      public final StringArrayParam outputCols()
      Description copied from interface: HasOutputCols
      Param for output column names.
      Specified by:
      outputCols in interface HasOutputCols
      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)

    • inputCols

      public final StringArrayParam inputCols()
      Description copied from interface: HasInputCols
      Param for input column names.
      Specified by:
      inputCols in interface HasInputCols
      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)

    • surrogateDF

      public Dataset<Row> surrogateDF()

    • setInputCol

      public ImputerModel setInputCol(String value)

    • setOutputCol

      public ImputerModel setOutputCol(String value)

    • setInputCols

      public ImputerModel setInputCols(String[] value)

    • setOutputCols

      public ImputerModel setOutputCols(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 ImputerModel 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<ImputerModel>
      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