Package smile.feature.transform

Class Normalizer

java.lang.Object

smile.feature.transform.Normalizer

All Implemented Interfaces:

Serializable, Function<Tuple,Tuple>, Transform

public class Normalizer
extends Object
implements 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:

• Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static enum	Normalizer.Norm	Vector norm.

Constructor Summary

Constructors

Constructor	Description
Normalizer(Normalizer.Norm norm, String... columns)	Constructor.

Method Summary

Modifier and Type	Method	Description
Tuple	apply(Tuple x)
String	toString()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.function.Function

andThen, compose

Methods inherited from interface smile.data.transform.Transform

andThen, apply, compose

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 Tuple apply(Tuple x)

Specified by:

apply in interface Function<Tuple,Tuple>

toString

public String toString()

Overrides:

toString in class Object