smile.feature

Class MaxAbsScaler

java.lang.Object

smile.feature.MaxAbsScaler

All Implemented Interfaces:

java.io.Serializable, FeatureTransform

public class MaxAbsScaler
extends java.lang.Object
implements FeatureTransform

Scales each feature by its maximum absolute value. This class scales and translates each feature individually such that the maximal absolute value of each feature in the training set will be 1.0. It does not shift/center the data, and thus does not destroy any sparsity.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected smile.data.type.StructType	schema The schema of data.

Constructor Summary

Constructors

Constructor and Description
MaxAbsScaler(smile.data.type.StructType schema, double[] scale) Constructor.

Method Summary

Modifier and Type	Method and Description
static MaxAbsScaler	fit(smile.data.DataFrame data) Learns transformation parameters from a dataset.
static MaxAbsScaler	fit(double[][] data) Learns transformation parameters from a dataset.
java.lang.String	toString()
smile.data.DataFrame	transform(smile.data.DataFrame data) Transform a data frame.
double[]	transform(double[] x) Transform a feature vector.
smile.data.Tuple	transform(smile.data.Tuple x) Transform a feature vector.

Methods inherited from class java.lang.Object

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

Methods inherited from interface smile.feature.FeatureTransform

transform

Field Detail

schema

protected smile.data.type.StructType schema

The schema of data.

Constructor Detail

MaxAbsScaler

public MaxAbsScaler(smile.data.type.StructType schema,
                    double[] scale)

Constructor.

Parameters:

schema - the schema of data.

scale - the scaling factor.

Method Detail

fit

public static MaxAbsScaler fit(smile.data.DataFrame data)

Learns transformation parameters from a dataset.

Parameters:

data - The training data.

fit

public static MaxAbsScaler fit(double[][] data)

Learns transformation parameters from a dataset.

Parameters:

data - The training data.

transform

public double[] transform(double[] x)

Description copied from interface: FeatureTransform

Transform a feature vector.

Specified by:

transform in interface FeatureTransform

Parameters:

x - a feature vector.

Returns:

the transformed feature value.

transform

public smile.data.Tuple transform(smile.data.Tuple x)

Description copied from interface: FeatureTransform

Transform a feature vector.

Specified by:

transform in interface FeatureTransform

Parameters:

x - a feature vector.

Returns:

the transformed feature value.

transform

public smile.data.DataFrame transform(smile.data.DataFrame data)

Description copied from interface: FeatureTransform

Transform a data frame.

Specified by:

transform in interface FeatureTransform

Parameters:

data - a data frame.

Returns:

the transformed data frame.

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object