mulan.classifier.meta
Class RAkELd

java.lang.Object
  mulan.classifier.MultiLabelLearnerBase
      mulan.classifier.meta.MultiLabelMetaLearner
          mulan.classifier.meta.RAkELd

All Implemented Interfaces:

Serializable, MultiLabelLearner, TechnicalInformationHandler

public class RAkELd
extends MultiLabelMetaLearner

Class implementing a generalized version of the RAkEL-d (RAndom k-labELsets) algorithm with disjoint labelsets. For more information, see

Grigorios Tsoumakas, Ioannis Katakis, Ioannis Vlahavas (2011). Random k-Labelsets for Multi-Label Classification. IEEE Transactions on Knowledge and Data Engineering. 23(7):1079-1089.

BibTeX:

 @article{Tsoumakas2011,
    author = {Grigorios Tsoumakas and Ioannis Katakis and Ioannis Vlahavas},
    journal = {IEEE Transactions on Knowledge and Data Engineering},
    number = {7},
    pages = {1079-1089},
    title = {Random k-Labelsets for Multi-Label Classification},
    volume = {23},
    year = {2011}
 }
 

Version:

2012.07.16

Author:

Ioannis Katakis, Grigorios Tsoumakas

See Also:

Serialized Form

Field Summary

Fields inherited from class mulan.classifier.meta.MultiLabelMetaLearner

baseLearner

Fields inherited from class mulan.classifier.MultiLabelLearnerBase

featureIndices, labelIndices, numLabels

Constructor Summary

RAkELd()
Default constructor

RAkELd(MultiLabelLearner baseLearner)
Construct a new instance based on the given multi-label learner

RAkELd(MultiLabelLearner baseLearner, int subset)
Constructs a new instance based on the given multi-label learner and size of subset

Method Summary

protected void	buildInternal(MultiLabelInstances trainingData) Learner specific implementation of building the model from MultiLabelInstances training data set.
int	getSizeOfSubset() Returns the size of the subsets
TechnicalInformation	getTechnicalInformation() Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
String	globalInfo() Returns a string describing classifier
protected MultiLabelOutput	makePredictionInternal(Instance instance) Learner specific implementation for predicting on specified data based on trained model.
void	setSeed(int x) Sets the seed for random number generation
void	setSizeOfSubset(int size) Sets the size of the subsets
void	updateClassifier(MultiLabelInstances mlTrainData, int model) Updates the current ensemble by training a specific classifier

Methods inherited from class mulan.classifier.meta.MultiLabelMetaLearner

getBaseLearner

Methods inherited from class mulan.classifier.MultiLabelLearnerBase

build, debug, getDebug, isModelInitialized, isUpdatable, makeCopy, makePrediction, setDebug

Methods inherited from class java.lang.Object

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

Constructor Detail

RAkELd

public RAkELd()

Default constructor

RAkELd

public RAkELd(MultiLabelLearner baseLearner)

Construct a new instance based on the given multi-label learner

Parameters:

baseLearner - a multi-label learner

RAkELd

public RAkELd(MultiLabelLearner baseLearner,
              int subset)

Constructs a new instance based on the given multi-label learner and size of subset

Parameters:

baseLearner - the multi-label learner

subset - the size of the subset

Method Detail

getTechnicalInformation

public TechnicalInformation getTechnicalInformation()

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

Specified by:

getTechnicalInformation in interface TechnicalInformationHandler

Specified by:

getTechnicalInformation in class MultiLabelLearnerBase

Returns:

the technical information about this class

setSeed

public void setSeed(int x)

Sets the seed for random number generation

Parameters:

x - the seed

setSizeOfSubset

public void setSizeOfSubset(int size)

Sets the size of the subsets

Parameters:

size - size of subsets

getSizeOfSubset

public int getSizeOfSubset()

Returns the size of the subsets

Returns:

the size of the subsets

buildInternal

protected void buildInternal(MultiLabelInstances trainingData)
                      throws Exception

Description copied from class: MultiLabelLearnerBase

Learner specific implementation of building the model from MultiLabelInstances training data set. This method is called from MultiLabelLearnerBase.build(MultiLabelInstances) method, where behavior common across all learners is applied.

Specified by:

buildInternal in class MultiLabelLearnerBase

Parameters:

trainingData - the training data set

Throws:

Exception - if learner model was not created successfully

updateClassifier

public void updateClassifier(MultiLabelInstances mlTrainData,
                             int model)
                      throws Exception

Updates the current ensemble by training a specific classifier

Parameters:

mlTrainData - the training data

model - the model to train

Throws:

Exception

makePredictionInternal

protected MultiLabelOutput makePredictionInternal(Instance instance)
                                           throws Exception

Description copied from class: MultiLabelLearnerBase

Learner specific implementation for predicting on specified data based on trained model. This method is called from MultiLabelLearnerBase.makePrediction(weka.core.Instance) which guards for model initialization and apply common handling/behavior.

Specified by:

makePredictionInternal in class MultiLabelLearnerBase

Parameters:

instance - the data instance to predict on

Returns:

the output of the learner for the given instance

Throws:

Exception - if an error occurs while making the prediction.

InvalidDataException - if specified instance data is invalid and can not be processed by the learner

globalInfo

public String globalInfo()

Returns a string describing classifier

Specified by:

globalInfo in class MultiLabelLearnerBase

Returns:

a description suitable for displaying