gov.sandia.cognition.learning.data.feature

Class RandomSubspace

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.util.AbstractRandomized

gov.sandia.cognition.learning.data.feature.RandomSubspace

All Implemented Interfaces:

BatchLearner<java.util.Collection<? extends Vectorizable>,SubVectorEvaluator>, VectorFactoryContainer, CloneableSerializable, Randomized, java.io.Serializable, java.lang.Cloneable

@PublicationReference(title="Random Subspace Method",
                      author="Wikipedia",
                      year=2011,
                      type=WebPage,
                      url="http://en.wikipedia.org/wiki/Random_subspace_method")
public class RandomSubspace
extends AbstractRandomized
implements BatchLearner<java.util.Collection<? extends Vectorizable>,SubVectorEvaluator>, Randomized, VectorFactoryContainer

Selects a random subspace from the given vector, which is a random set of indices. It is typically used in the context of ensemble learning to adapt a base learner to increase the variance, similar to the method used in bagging or random forests. Thus, it is also known as attribute bagging.

Since:

3.3.3

Author:

Justin Basilico

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static int	DEFAULT_SIZE The default size is 10.
protected int	size The size of the random subspace to create, which is the number of dimensions that are chosen.
protected VectorFactory<?>	vectorFactory The vector factory for the sub vector evaluator to use.

Fields inherited from class gov.sandia.cognition.util.AbstractRandomized

random

Constructor Summary

Constructors

Constructor and Description
RandomSubspace() Creates a new RandomSubspace with the default size.
RandomSubspace(int size) Creates a new RandomSubspace with the given size.
RandomSubspace(int size, java.util.Random random) Creates a new RandomSubspace with the given parameters.
RandomSubspace(int size, java.util.Random random, VectorFactory<?> vectorFactory) Creates a new RandomSubspace with the given parameters.

Method Summary

Modifier and Type	Method and Description
int	getSize() Gets the size of the subspace that will be created.
VectorFactory<? extends Vector>	getVectorFactory() Gets the vector factory the object to use to create new vectors.
SubVectorEvaluator	learn(java.util.Collection<? extends Vectorizable> data) The learn method creates an object of ResultType using data of type DataType, using some form of "learning" algorithm.
void	setSize(int size) Sets the size of the subspace that will be created.
void	setVectorFactory(VectorFactory<?> vectorFactory) Sets the vector factory to use.

Methods inherited from class gov.sandia.cognition.util.AbstractRandomized

clone, getRandom, setRandom

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Methods inherited from interface gov.sandia.cognition.util.Randomized

getRandom, setRandom

Field Detail

DEFAULT_SIZE

public static final int DEFAULT_SIZE

The default size is 10.

See Also:

Constant Field Values

size

protected int size

The size of the random subspace to create, which is the number of dimensions that are chosen.

vectorFactory

protected VectorFactory<?> vectorFactory

The vector factory for the sub vector evaluator to use.

Constructor Detail

RandomSubspace

public RandomSubspace()

Creates a new RandomSubspace with the default size.

RandomSubspace

public RandomSubspace(int size)

Creates a new RandomSubspace with the given size.

Parameters:

size - The size of the subspace to create. Must be positive.

RandomSubspace

public RandomSubspace(int size,
                      java.util.Random random)

Creates a new RandomSubspace with the given parameters.

Parameters:

size - The size of the subspace to create. Must be positive.

random - The random number generator to use.

RandomSubspace

public RandomSubspace(int size,
                      java.util.Random random,
                      VectorFactory<?> vectorFactory)

Creates a new RandomSubspace with the given parameters.

Parameters:

size - The size of the subspace to create. Must be positive.

random - The random number generator to use.

vectorFactory - The vector factory to use in the result to create

Method Detail

learn

public SubVectorEvaluator learn(java.util.Collection<? extends Vectorizable> data)

Description copied from interface: BatchLearner

The learn method creates an object of ResultType using data of type DataType, using some form of "learning" algorithm.

Specified by:

learn in interface BatchLearner<java.util.Collection<? extends Vectorizable>,SubVectorEvaluator>

Parameters:

data - The data that the learning algorithm will use to create an object of ResultType.

Returns:

The object that is created based on the given data using the learning algorithm.

getSize

public int getSize()

Gets the size of the subspace that will be created.

Returns:

The size of the subspace that will be created. Must be positive.

setSize

public void setSize(int size)

Sets the size of the subspace that will be created.

Parameters:

size - The size of the subspace that will be created. Must be positive.

getVectorFactory

public VectorFactory<? extends Vector> getVectorFactory()

Description copied from interface: VectorFactoryContainer

Gets the vector factory the object to use to create new vectors.

Specified by:

getVectorFactory in interface VectorFactoryContainer

Returns:

The vector factory.

setVectorFactory

public void setVectorFactory(VectorFactory<?> vectorFactory)

Sets the vector factory to use.

Parameters:

vectorFactory - The vector factory to use.