it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm

Class Stoptron

java.lang.Object

it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm.BudgetedLearningAlgorithm

it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm.Stoptron

All Implemented Interfaces:

BinaryLearningAlgorithm, KernelMethod, LearningAlgorithm, MetaLearningAlgorithm, OnlineLearningAlgorithm

public class Stoptron
extends BudgetedLearningAlgorithm
implements MetaLearningAlgorithm

It is a variation of the Stoptron proposed in

[OrabonaICML2008] Francesco Orabona, Joseph Keshet, and Barbara Caputo. The projectron: a bounded kernel-based perceptron. In Int. Conf. on Machine Learning (2008)

Until the budget is not reached the online learning updating policy is the one of the baseAlgorithm that this meta-algorithm is exploiting. When the budget is full, the learning process ends

Author:

Simone Filice

Field Summary

Fields inherited from class it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm.BudgetedLearningAlgorithm

budget, label

Constructor Summary

Constructors

Constructor and Description
Stoptron()
Stoptron(int budget, OnlineLearningAlgorithm baseAlgorithm, Label label)

Method Summary

Methods

Modifier and Type	Method and Description
Stoptron	duplicate() Creates a new instance of the LearningAlgorithm initialized with the same parameters of the learningAlgorithm to be duplicated.
OnlineLearningAlgorithm	getBaseAlgorithm() Returns the base algorithm this meta algorithm is based on
Kernel	getKernel() Returns the kernel exploited by this learner
PredictionFunction	getPredictionFunction() Returns the predictionFunction learned during the training process
protected Prediction	predictAndLearnWithAvailableBudget(Example example)
protected Prediction	predictAndLearnWithFullBudget(Example example) Learns from a single example applying a specific policy that must be adopted when the budget is reached
void	reset() Resets all the learning process, returning to the default state.
void	setBaseAlgorithm(LearningAlgorithm baseAlgorithm)
void	setKernel(Kernel kernel) Sets the kernel this
void	setPredictionFunction(PredictionFunction predictionFunction) Sets the predictionFunction learned during the training process.

Methods inherited from class it.uniroma2.sag.kelp.learningalgorithm.budgetedAlgorithm.BudgetedLearningAlgorithm

getBudget, getLabel, getLabels, learn, learn, setBudget, setLabel, setLabels

Methods inherited from class java.lang.Object

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

Methods inherited from interface it.uniroma2.sag.kelp.learningalgorithm.LearningAlgorithm

getLabels, learn, setLabels

Constructor Detail

Stoptron

public Stoptron()

Stoptron

public Stoptron(int budget,
        OnlineLearningAlgorithm baseAlgorithm,
        Label label)

Method Detail

duplicate

public Stoptron duplicate()

Description copied from interface: LearningAlgorithm

Creates a new instance of the LearningAlgorithm initialized with the same parameters of the learningAlgorithm to be duplicated. A shallow copy of the learning parameters is performed, while the state parameters are initialized to their default value. The labels are not initialized neither copied

Specified by:

duplicate in interface LearningAlgorithm

reset

public void reset()

Description copied from interface: LearningAlgorithm

Resets all the learning process, returning to the default state. All the learned process is forgotten

Specified by:

reset in interface LearningAlgorithm

predictAndLearnWithFullBudget

protected Prediction predictAndLearnWithFullBudget(Example example)

Description copied from class: BudgetedLearningAlgorithm

Learns from a single example applying a specific policy that must be adopted when the budget is reached

Specified by:

predictAndLearnWithFullBudget in class BudgetedLearningAlgorithm

Parameters:

example - the example to be exploited in the learning process

Returns:

the prediction on the given example, using the old classification function (before any possible update)

setBaseAlgorithm

public void setBaseAlgorithm(LearningAlgorithm baseAlgorithm)

Specified by:

setBaseAlgorithm in interface MetaLearningAlgorithm

Parameters:

baseAlgorithm - the baseAlgorithm to set

getBaseAlgorithm

public OnlineLearningAlgorithm getBaseAlgorithm()

Description copied from interface: MetaLearningAlgorithm

Returns the base algorithm this meta algorithm is based on

Specified by:

getBaseAlgorithm in interface MetaLearningAlgorithm

Returns:

the base algorithm

getPredictionFunction

public PredictionFunction getPredictionFunction()

Description copied from interface: LearningAlgorithm

Returns the predictionFunction learned during the training process

Specified by:

getPredictionFunction in interface LearningAlgorithm

Returns:

the predictionFunction learned during the training process

getKernel

public Kernel getKernel()

Description copied from interface: KernelMethod

Returns the kernel exploited by this learner

Specified by:

getKernel in interface KernelMethod

Returns:

the kernel

setKernel

public void setKernel(Kernel kernel)

Description copied from interface: KernelMethod

Sets the kernel this

Specified by:

setKernel in interface KernelMethod

Parameters:

kernel - the kernel to set

predictAndLearnWithAvailableBudget

protected Prediction predictAndLearnWithAvailableBudget(Example example)

Specified by:

predictAndLearnWithAvailableBudget in class BudgetedLearningAlgorithm

setPredictionFunction

public void setPredictionFunction(PredictionFunction predictionFunction)

Description copied from interface: LearningAlgorithm

Sets the predictionFunction learned during the training process. It can be used to change the default prediction function, or to set an already trained one.

Specified by:

setPredictionFunction in interface LearningAlgorithm