mulan.classifier.meta.thresholding
Class MetaLabeler

java.lang.Object
  mulan.classifier.MultiLabelLearnerBase
      mulan.classifier.meta.MultiLabelMetaLearner
          mulan.classifier.meta.thresholding.Meta
              mulan.classifier.meta.thresholding.MetaLabeler

All Implemented Interfaces:

Serializable, MultiLabelLearner, TechnicalInformationHandler

public class MetaLabeler
extends Meta

Class implementing the MetaLabeler algorithm. For more information, see

Lei Tang, Sugu Rajan, Yijay K. Narayanan: Large scale multi-label classification via metalabeler. In: Proceedings of the 18th international conference on World wide web , 211-220, 2009.

BibTeX:

 @inproceedings{Tang2009,
    author = {Lei Tang and Sugu Rajan and Yijay K. Narayanan},
    booktitle = {Proceedings of the 18th international conference on World wide web },
    pages = {211-220},
    title = {Large scale multi-label classification via metalabeler},
    year = {2009},
    location = {Madrid, Spain}
 }
 

Version:

2010.12.14

Author:

Marios Ioannou, George Sakkas, Grigorios Tsoumakas

See Also:

Serialized Form

Field Summary

Fields inherited from class mulan.classifier.meta.thresholding.Meta

classifier, classifierInstances, foldLearner, kFoldsCV, metaDatasetChoice

Fields inherited from class mulan.classifier.meta.MultiLabelMetaLearner

baseLearner

Fields inherited from class mulan.classifier.MultiLabelLearnerBase

featureIndices, labelIndices, numLabels

Constructor Summary

MetaLabeler()
Default constructor

MetaLabeler(MultiLabelLearner baseLearner, Classifier classifier, String metaDataChoice, String aClassChoice)
Constructor that initializes the learner

Method Summary

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 the multi-label learner.
protected MultiLabelOutput	makePredictionInternal(Instance instance) Learner specific implementation for predicting on specified data based on trained model.
void	setFolds(int f) Sets the number of folds for internal cv
protected Instances	transformData(MultiLabelInstances trainingData) abstract method that transforms the training data to meta data

Methods inherited from class mulan.classifier.meta.thresholding.Meta

buildInternal, getClassifier, modifiedInstanceX, prepareClassifierInstances, valuesX

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

MetaLabeler

public MetaLabeler()

Default constructor

MetaLabeler

public MetaLabeler(MultiLabelLearner baseLearner,
                   Classifier classifier,
                   String metaDataChoice,
                   String aClassChoice)

Constructor that initializes the learner

Parameters:

baseLearner - the underlying multi-label learner

classifier - the binary classification

metaDataChoice - the type of meta-data

aClassChoice - the type of the class

Method Detail

getTechnicalInformation

public TechnicalInformation getTechnicalInformation()

Description copied from class: MultiLabelLearnerBase

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

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

transformData

protected Instances transformData(MultiLabelInstances trainingData)
                           throws Exception

Description copied from class: Meta

abstract method that transforms the training data to meta data

Specified by:

transformData in class Meta

Parameters:

trainingData - the training data set

Returns:

the meta data for training the predictor of labels/threshold

Throws:

Exception

setFolds

public void setFolds(int f)

Sets the number of folds for internal cv

Parameters:

f - the number of folds

globalInfo

public String globalInfo()

Description copied from class: MultiLabelLearnerBase

Returns a string describing the multi-label learner.

Specified by:

globalInfo in class MultiLabelLearnerBase

Returns:

a description suitable for displaying in a future gui