it.uniroma2.sag.kelp.learningalgorithm

Class MultiEpochLearning

java.lang.Object

it.uniroma2.sag.kelp.learningalgorithm.MultiEpochLearning

All Implemented Interfaces:

LearningAlgorithm, MetaLearningAlgorithm

public class MultiEpochLearning
extends Object
implements MetaLearningAlgorithm

It is a meta learning algorithms for online learning methods. It performs multiple iterations on the training data

Author:

Simone Filice

Constructor Summary

Constructors

Constructor and Description
MultiEpochLearning()
MultiEpochLearning(int epochs, LearningAlgorithm baseAlgorithm)
MultiEpochLearning(int epochs, LearningAlgorithm baseAlgorithm, List<Label> labels)

Method Summary

Methods

Modifier and Type	Method and Description
MultiEpochLearning	duplicate() Creates a new instance of the LearningAlgorithm initialized with the same parameters of the learningAlgorithm to be duplicated.
LearningAlgorithm	getBaseAlgorithm() Returns the base algorithm this meta algorithm is based on
int	getEpochs()
List<Label>	getLabels() Returns the labels representing the concept to be learned.
PredictionFunction	getPredictionFunction() Returns the predictionFunction learned during the training process
void	learn(Dataset dataset) It starts the training process exploiting the provided dataset
void	reset() Resets all the learning process, returning to the default state.
void	setBaseAlgorithm(LearningAlgorithm baseAlgorithm)
void	setEpochs(int epochs)
void	setLabels(List<Label> labels) Sets the labels representing the concept to be learned.

Methods inherited from class java.lang.Object

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

Constructor Detail

MultiEpochLearning

public MultiEpochLearning()

MultiEpochLearning

public MultiEpochLearning(int epochs,
                  LearningAlgorithm baseAlgorithm,
                  List<Label> labels)

MultiEpochLearning

public MultiEpochLearning(int epochs,
                  LearningAlgorithm baseAlgorithm)

Method Detail

setBaseAlgorithm

public void setBaseAlgorithm(LearningAlgorithm baseAlgorithm)

Specified by:

setBaseAlgorithm in interface MetaLearningAlgorithm

Parameters:

baseAlgorithm - the baseAlgorithm to set

getBaseAlgorithm

public LearningAlgorithm 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

getEpochs

public int getEpochs()

Returns:

the number of epochs

setEpochs

public void setEpochs(int epochs)

Parameters:

epochs - the number of epochs to set

learn

public void learn(Dataset dataset)

Description copied from interface: LearningAlgorithm

It starts the training process exploiting the provided dataset

Specified by:

learn in interface LearningAlgorithm

Parameters:

dataset - the training data

setLabels

public void setLabels(List<Label> labels)

Description copied from interface: LearningAlgorithm

Sets the labels representing the concept to be learned.

Specified by:

setLabels in interface LearningAlgorithm

Parameters:

labels - the labels representing the concept to be learned

getLabels

public List<Label> getLabels()

Description copied from interface: LearningAlgorithm

Returns the labels representing the concept to be learned.

Specified by:

getLabels in interface LearningAlgorithm

Returns:

the labels representing the concept to be learned

duplicate

public MultiEpochLearning 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

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