mulan.classifier.meta.thresholding
Class OneThreshold

java.lang.Object
  mulan.classifier.MultiLabelLearnerBase
      mulan.classifier.meta.MultiLabelMetaLearner
          mulan.classifier.meta.thresholding.OneThreshold

All Implemented Interfaces:

Serializable, MultiLabelLearner, TechnicalInformationHandler

public class OneThreshold
extends MultiLabelMetaLearner

Class that estimates a single threshold for all labels and examples. For more information, see

Read, Jesse, Pfahringer, Bernhard, Holmes, Geoff: Multi-label Classification Using Ensembles of Pruned Sets. In: Data Mining, 2008. ICDM '08. Eighth IEEE International Conference on, 995-1000, 2008.

BibTeX:

 @inproceedings{Read2008,
    author = {Read, Jesse and Pfahringer, Bernhard and Holmes, Geoff},
    booktitle = {Data Mining, 2008. ICDM '08. Eighth IEEE International Conference on},
    pages = {995-1000},
    title = {Multi-label Classification Using Ensembles of Pruned Sets},
    year = {2008},
    location = {Pisa, Italy}
 }
 

Version:

2010.12.14

Author:

Marios Ioannou, George Sakkas, 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

OneThreshold()
Default constructor

OneThreshold(MultiLabelLearner baseLearner, BipartitionMeasureBase aMeasure)

OneThreshold(MultiLabelLearner baseLearner, BipartitionMeasureBase aMeasure, int someFolds)

Method Summary

protected void	buildInternal(MultiLabelInstances trainingData) Learner specific implementation of building the model from MultiLabelInstances training data set.
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.
double	getThreshold() Returns the calculated threshold
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.

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

OneThreshold

public OneThreshold()

Default constructor

OneThreshold

public OneThreshold(MultiLabelLearner baseLearner,
                    BipartitionMeasureBase aMeasure,
                    int someFolds)

Parameters:

baseLearner - the underlying multi=label learner

aMeasure - the measure to optimize

someFolds - number of cross-validation folds

OneThreshold

public OneThreshold(MultiLabelLearner baseLearner,
                    BipartitionMeasureBase aMeasure)

Parameters:

baseLearner - the underlying multi=label learner

aMeasure - measure to optimize

Method Detail

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

makePredictionInternal

protected MultiLabelOutput makePredictionInternal(Instance instance)
                                           throws Exception,
                                                  InvalidDataException

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

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

getThreshold

public double getThreshold()

Returns the calculated threshold

Returns:

the calculated threshold

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