org.lenskit.transform.normalize

Class MeanCenteringVectorNormalizer

• All Implemented Interfaces:
Serializable, VectorNormalizer

@Shareable
public class MeanCenteringVectorNormalizer
extends AbstractVectorNormalizer
implements Serializable

Vector normlizer that subtracts the mean from every value.

Serialized Form
• Constructor Summary

Constructors
Constructor and Description
MeanCenteringVectorNormalizer()
• Method Summary

All Methods
Modifier and Type Method and Description
InvertibleFunction<Long2DoubleMap,Long2DoubleMap> makeTransformation(Long2DoubleMap reference)
Create a vector transformation that normalizes and denormalizes vectors with respect to a reference vector.
VectorTransformation makeTransformation(SparseVector reference)
Create a vector transformation that normalizes and denormalizes vectors with respect to the specified entity.
• Methods inherited from class org.lenskit.transform.normalize.AbstractVectorNormalizer

normalize
• Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
• Constructor Detail

• MeanCenteringVectorNormalizer

public MeanCenteringVectorNormalizer()
• Method Detail

• makeTransformation

public VectorTransformation makeTransformation(SparseVector reference)
Description copied from interface: VectorNormalizer

Create a vector transformation that normalizes and denormalizes vectors with respect to the specified entity. This allows transformations to be applied multiple times to different vectors and also unapplied.

If the reference vector is empty, the returned transformation should be the identity transform. Results are undefined if the reference vector is not complete or contains NaN values.

If the normalization needs to retain a copy of the sparse vector, it will take an immutable copy.

Specified by:
makeTransformation in interface VectorNormalizer
Parameters:
reference - The reference vector.
Returns:
A transformation built from the reference vector.
• makeTransformation

public InvertibleFunction<Long2DoubleMap,Long2DoubleMap> makeTransformation(Long2DoubleMap reference)
Description copied from interface: VectorNormalizer

Create a vector transformation that normalizes and denormalizes vectors with respect to a reference vector. The reference vector is used to compute any data needed for the normalization. For example, a mean-centering normalization will subtract the mean of the reference vector from any vector to which it is applied, and add back the reference mean when it is unapplied.

This allows transformations to be applied multiple times to different vectors and also unapplied.

If the reference vector is empty, the returned transformation should be the identity transform. Results are undefined if the reference vector is not complete or contains NaN values.

If the normalization needs to retain a copy of the sparse vector, it will take an immutable copy.

Specified by:
makeTransformation in interface VectorNormalizer
Parameters:
reference - The reference vector.
Returns:
A transformation built from the reference vector.