gov.sandia.cognition.learning.algorithm.perceptron

Class OnlineMultiPerceptron.UniformUpdate<CategoryType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner<InputOutputPair<? extends Vectorizable,CategoryType>,LinearMultiCategorizer<CategoryType>>

gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron<CategoryType>

gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron.UniformUpdate<CategoryType>

Type Parameters:

CategoryType - The type of output categories. Can be any type that has a valid equals and hashCode method.

All Implemented Interfaces:

BatchAndIncrementalLearner<InputOutputPair<? extends Vectorizable,CategoryType>,LinearMultiCategorizer<CategoryType>>, BatchLearner<java.util.Collection<? extends InputOutputPair<? extends Vectorizable,CategoryType>>,LinearMultiCategorizer<CategoryType>>, IncrementalLearner<InputOutputPair<? extends Vectorizable,CategoryType>,LinearMultiCategorizer<CategoryType>>, VectorFactoryContainer, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

OnlineMultiPerceptron<CategoryType>

@PublicationReference(title="Ultraconservative online algorithms for multiclass problems",
                      author={"Koby Crammer","Yoram Singer"},
                      year=2003,
                      type=Journal,
                      publication="The Journal of Machine Learning Research",
                      pages={951,991},
                      url="http://portal.acm.org/citation.cfm?id=944936")
public static class OnlineMultiPerceptron.UniformUpdate<CategoryType>
extends OnlineMultiPerceptron<CategoryType>

Variant of a multi-category Perceptron that performs a uniform weight update on all categories that are scored higher than the true category such that the weights are equal and sum to -1.

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron

OnlineMultiPerceptron.ProportionalUpdate<CategoryType>, OnlineMultiPerceptron.UniformUpdate<CategoryType>

Field Summary

Fields inherited from class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron

DEFAULT_MIN_MARGIN, minMargin, vectorFactory

Constructor Summary

Constructors

Constructor and Description
UniformUpdate() Creates a new OnlineMultiPerceptron.UniformUpdate.
UniformUpdate(double minMargin) Creates a new OnlineMultiPerceptron.UniformUpdate with the given minimum margin.
UniformUpdate(double minMargin, VectorFactory<?> vectorFactory) Creates a new OnlineMultiPerceptron.UniformUpdate with the given minimum margin and backing vector factory.

Method Summary

Modifier and Type	Method and Description
void	update(LinearMultiCategorizer<CategoryType> target, InputOutputPair<? extends Vectorizable,CategoryType> example) The update method updates an object of ResultType using the given new data of type DataType, using some form of "learning" algorithm.

Methods inherited from class gov.sandia.cognition.learning.algorithm.perceptron.OnlineMultiPerceptron

createInitialLearnedObject, getMinMargin, getVectorFactory, setMinMargin, setVectorFactory

Methods inherited from class gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner

clone, learn, learn, update

Methods inherited from class java.lang.Object

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

Constructor Detail

UniformUpdate

public UniformUpdate()

Creates a new OnlineMultiPerceptron.UniformUpdate.

UniformUpdate

public UniformUpdate(double minMargin)

Creates a new OnlineMultiPerceptron.UniformUpdate with the given minimum margin.

Parameters:

minMargin - The minimum margin to consider an example correct.

UniformUpdate

public UniformUpdate(double minMargin,
                     VectorFactory<?> vectorFactory)

Creates a new OnlineMultiPerceptron.UniformUpdate with the given minimum margin and backing vector factory.

Parameters:

minMargin - The minimum margin to consider an example correct.

vectorFactory - The vector factory used to create the weight vectors.

Method Detail

update

public void update(LinearMultiCategorizer<CategoryType> target,
                   InputOutputPair<? extends Vectorizable,CategoryType> example)

Description copied from interface: IncrementalLearner

The update method updates an object of ResultType using the given new data of type DataType, using some form of "learning" algorithm.

Specified by:

update in interface IncrementalLearner<InputOutputPair<? extends Vectorizable,CategoryType>,LinearMultiCategorizer<CategoryType>>

Overrides:

update in class OnlineMultiPerceptron<CategoryType>

Parameters:

target - The object to update.

example - The new data for the learning algorithm to use to update the object.