Package org.apache.spark.ml.feature

Class Binarizer

Object
org.apache.spark.ml.PipelineStage
org.apache.spark.ml.Transformer
org.apache.spark.ml.feature.Binarizer
All Implemented Interfaces:
Serializable, org.apache.spark.internal.Logging, Params, HasInputCol, HasInputCols, HasOutputCol, HasOutputCols, HasThreshold, HasThresholds, DefaultParamsWritable, Identifiable, MLWritable
public final class Binarizer extends Transformer implements HasThreshold, HasThresholds, HasInputCol, HasOutputCol, HasInputCols, HasOutputCols, DefaultParamsWritable
Binarize a column of continuous features given a threshold.

Since 3.0.0, Binarize can map multiple columns at once by setting the inputCols parameter. Note that when both the inputCol and inputCols parameters are set, an Exception will be thrown. The threshold parameter is used for single column usage, and thresholds is for multiple columns.

See Also:

  • Constructor Details

    • Binarizer

      public Binarizer(String uid)

    • Binarizer

      public Binarizer()

  • Method Details

    • load

      public static Binarizer load(String path)

    • read

      public static MLReader<T> read()

    • outputCols

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

    • 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)

    • threshold

      public DoubleParam threshold()
      Param for threshold used to binarize continuous features. The features greater than the threshold, will be binarized to 1.0. The features equal to or less than the threshold, will be binarized to 0.0. Default: 0.0
      Specified by:
      threshold in interface HasThreshold
      Returns:
      (undocumented)

    • setThreshold

      public Binarizer setThreshold(double value)

    • thresholds

      public DoubleArrayParam thresholds()
      Array of threshold used to binarize continuous features. This is for multiple columns input. If transforming multiple columns and thresholds is not set, but threshold is set, then threshold will be applied across all columns.

      Specified by:
      thresholds in interface HasThresholds
      Returns:
      (undocumented)

    • setThresholds

      public Binarizer setThresholds(double[] value)

    • setInputCol

      public Binarizer setInputCol(String value)

    • setOutputCol

      public Binarizer setOutputCol(String value)

    • setInputCols

      public Binarizer setInputCols(String[] value)

    • setOutputCols

      public Binarizer 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 Binarizer 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 Transformer
      Parameters:
      extra - (undocumented)
      Returns:
      (undocumented)

    • toString

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