gov.sandia.cognition.learning.algorithm.perceptron.kernel

Class Projectron.LinearSoftMargin<InputType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner<InputOutputPair<? extends InputType,OutputType>,ResultType>

gov.sandia.cognition.learning.algorithm.AbstractSupervisedBatchAndIncrementalLearner<InputType,java.lang.Boolean,DefaultKernelBinaryCategorizer<InputType>>

gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineKernelBinaryCategorizerLearner<InputType>

gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron<InputType>

gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron.LinearSoftMargin<InputType>

Type Parameters:

InputType - The type of input to learn over. Passed to the kernel function.

All Implemented Interfaces:

BatchAndIncrementalLearner<InputOutputPair<? extends InputType,java.lang.Boolean>,DefaultKernelBinaryCategorizer<InputType>>, BatchLearner<java.util.Collection<? extends InputOutputPair<? extends InputType,java.lang.Boolean>>,DefaultKernelBinaryCategorizer<InputType>>, IncrementalLearner<InputOutputPair<? extends InputType,java.lang.Boolean>,DefaultKernelBinaryCategorizer<InputType>>, SupervisedBatchAndIncrementalLearner<InputType,java.lang.Boolean,DefaultKernelBinaryCategorizer<InputType>>, SupervisedBatchLearner<InputType,java.lang.Boolean,DefaultKernelBinaryCategorizer<InputType>>, SupervisedIncrementalLearner<InputType,java.lang.Boolean,DefaultKernelBinaryCategorizer<InputType>>, KernelContainer<InputType>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

Projectron<InputType>

@PublicationReference(author={"Francesco Orabona","Joseph Keshet","Barbara Caputo"},
                      title="Bounded Kernel-Based Online Learning",
                      year=2009,
                      type=Journal,
                      publication="Journal of Machine Learning Research",
                      pages={2643,2666},
                      url="http://portal.acm.org/citation.cfm?id=1755875",
                      notes="This is the Projectron++.")
public static class Projectron.LinearSoftMargin<InputType>
extends Projectron<InputType>

An implementation of the Projectron++ algorithm, which is an online kernel binary categorizer learner that has a budget parameter tuned by the eta parameter. It is an extension of the Projectron algorithm inspired by the Passive Aggressive I algorithm (PA-I), which uses a linear soft margin constraint. This is why the class is named LinearSoftMargin, like the PA-I implementation.

Since:

3.3.0

Author:

Justin Basilico

See Also:

Serialized Form

Nested Class Summary

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

Projectron.LinearSoftMargin<InputType>

Field Summary

Fields inherited from class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron

DEFAULT_ETA, eta

Fields inherited from class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineKernelBinaryCategorizerLearner

kernel

Constructor Summary

Constructors

Constructor and Description
LinearSoftMargin() Creates a new Projectron.LinearSoftMargin with a null kernel and default parameters.
LinearSoftMargin(Kernel<? super InputType> kernel) Creates a new Projectron.LinearSoftMargin with the given kernel and default parameters.
LinearSoftMargin(Kernel<? super InputType> kernel, double eta) Creates a new Projectron.LinearSoftMargin with the given parameters.

Method Summary

Modifier and Type	Method and Description
protected void	applyUpdate(DefaultKernelBinaryCategorizer<InputType> target, InputType input, double actual, double margin, double kernelInputInput, double delta, Vector d) Apply the update for the Projectron.
protected boolean	shouldUpdate(double margin) Determine if an update should be made.

Methods inherited from class gov.sandia.cognition.learning.algorithm.perceptron.kernel.Projectron

getEta, setEta, update

Methods inherited from class gov.sandia.cognition.learning.algorithm.perceptron.kernel.AbstractOnlineKernelBinaryCategorizerLearner

createInitialLearnedObject, getKernel, setKernel, update

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

update

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

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

clone

Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchAndIncrementalLearner

learn

Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchLearner

learn

Methods inherited from interface gov.sandia.cognition.learning.algorithm.IncrementalLearner

update

Constructor Detail

LinearSoftMargin

public LinearSoftMargin()

Creates a new Projectron.LinearSoftMargin with a null kernel and default parameters.

LinearSoftMargin

public LinearSoftMargin(Kernel<? super InputType> kernel)

Creates a new Projectron.LinearSoftMargin with the given kernel and default parameters.

Parameters:

kernel - The kernel to use.

LinearSoftMargin

public LinearSoftMargin(Kernel<? super InputType> kernel,
                        double eta)

Creates a new Projectron.LinearSoftMargin with the given parameters.

Parameters:

kernel - The kernel to use.

eta - The eta parameter, which controls the number of supports created. Must be non-negative.

Method Detail

shouldUpdate

protected boolean shouldUpdate(double margin)

Description copied from class: Projectron

Determine if an update should be made. This is here so that the Projectron++ implementation can override it to provide a margin update.

Overrides:

shouldUpdate in class Projectron<InputType>

Parameters:

margin - The margin.

Returns:

A determination of whether or not an update should be made based on the margin.

applyUpdate

protected void applyUpdate(DefaultKernelBinaryCategorizer<InputType> target,
                           InputType input,
                           double actual,
                           double margin,
                           double kernelInputInput,
                           double delta,
                           Vector d)

Description copied from class: Projectron

Apply the update for the Projectron. This function is put here so that it can be overriden by the Projectron++ implementation, which also enforces a margin.

Overrides:

applyUpdate in class Projectron<InputType>

Parameters:

target - The target to update.

input - The input value.

actual - The actual label.

margin - The margin on the input.

kernelInputInput - The kernel function k(input, input).

delta - The value delta computed by the Projectron.

d - The vector d that represents the coefficients for the projection.