Class Normalizer

java.lang.Object
smile.feature.transform.Normalizer
All Implemented Interfaces:
Serializable, Function<smile.data.Tuple,smile.data.Tuple>, smile.data.transform.Transform

public class Normalizer extends Object implements smile.data.transform.Transform
Normalize samples individually to unit norm. Each sample (i.e. each row of the data matrix) with at least one non-zero component is rescaled independently of other samples so that its norm (L1 or L2) equals one.

Scaling inputs to unit norms is a common operation for text classification or clustering for instance.

See Also:
  • Constructor Details

    • Normalizer

      public Normalizer(Normalizer.Norm norm, String... columns)
      Constructor.
      Parameters:
      norm - the vector norm.
      columns - the columns to transform.
  • Method Details

    • apply

      public smile.data.Tuple apply(smile.data.Tuple x)
      Specified by:
      apply in interface Function<smile.data.Tuple,smile.data.Tuple>
    • toString

      public String toString()
      Overrides:
      toString in class Object