Package org.apache.spark.ml.feature

Class StandardScaler

Object
org.apache.spark.ml.PipelineStage
org.apache.spark.ml.Estimator<StandardScalerModel>
org.apache.spark.ml.feature.StandardScaler
All Implemented Interfaces:
Serializable, org.apache.spark.internal.Logging, StandardScalerParams, Params, HasInputCol, HasOutputCol, DefaultParamsWritable, Identifiable, MLWritable, scala.Serializable
public class StandardScaler extends Estimator<StandardScalerModel> implements StandardScalerParams, DefaultParamsWritable
Standardizes features by removing the mean and scaling to unit variance using column summary statistics on the samples in the training set.

The "unit std" is computed using the corrected sample standard deviation, which is computed as the square root of the unbiased sample variance.

See Also:

  • Constructor Details

    • StandardScaler

      public StandardScaler(String uid)

    • StandardScaler

      public StandardScaler()

  • Method Details

    • load

      public static StandardScaler load(String path)

    • read

      public static MLReader<T> read()

    • withMean

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

    • withStd

      public BooleanParam withStd()
      Description copied from interface: StandardScalerParams
      Whether to scale the data to unit standard deviation. Default: true
      Specified by:
      withStd in interface StandardScalerParams
      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)

    • setInputCol

      public StandardScaler setInputCol(String value)

    • setOutputCol

      public StandardScaler setOutputCol(String value)

    • setWithMean

      public StandardScaler setWithMean(boolean value)

    • setWithStd

      public StandardScaler setWithStd(boolean value)

    • fit

      public StandardScalerModel fit(Dataset<?> dataset)
      Description copied from class: Estimator
      Fits a model to the input data.
      Specified by:
      fit in class Estimator<StandardScalerModel>
      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 StandardScaler 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 Estimator<StandardScalerModel>
      Parameters:
      extra - (undocumented)
      Returns:
      (undocumented)