mulan.classifier.lazy
Class IBLR_ML

java.lang.Object
  mulan.classifier.MultiLabelLearnerBase
      mulan.classifier.lazy.MultiLabelKNN
          mulan.classifier.lazy.IBLR_ML

All Implemented Interfaces:

Serializable, MultiLabelLearner, TechnicalInformationHandler

public class IBLR_ML
extends MultiLabelKNN

This class is an implementation of the "IBLR-ML" and "IBLR-ML+" methods for the MULAN package.

For more information, see

Weiwei Cheng, Eyke Hullermeier (2009). Combining instance-based learning and logistic regression for multilabel classification. Machine Learning. 76(2-3):211-225.

BibTeX:

 @article{Cheng2009,
    author = {Weiwei Cheng and Eyke Hullermeier},
    journal = {Machine Learning},
    number = {2-3},
    pages = {211-225},
    publisher = {Springer Netherlands},
    title = {Combining instance-based learning and logistic regression for multilabel classification},
    volume = {76},
    year = {2009},
    ISSN = {0885-6125}
 }
 

Version:

2010.12.29

Author:

Weiwei Cheng, Eleftherios Spyromitros-Xioufis, Grigorios Tsoumakas

See Also:

Serialized Form

Field Summary

Fields inherited from class mulan.classifier.lazy.MultiLabelKNN

dfunc, distanceWeighting, lnn, numOfNeighbors, train, WEIGHT_INVERSE, WEIGHT_NONE, WEIGHT_SIMILARITY

Fields inherited from class mulan.classifier.MultiLabelLearnerBase

featureIndices, labelIndices, numLabels

Constructor Summary

IBLR_ML()
Default constructor uses 10 NN

IBLR_ML(int numNeighbors)
Constructor that sets the number of neighbors

IBLR_ML(int numNeighbors, boolean addFeatures)
Full constructor

Method Summary

protected void	buildInternal(MultiLabelInstances mltrain) 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.
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.lazy.MultiLabelKNN

isUpdatable, setDfunc, setDistanceWeighting

Methods inherited from class mulan.classifier.MultiLabelLearnerBase

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

Methods inherited from class java.lang.Object

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

Constructor Detail

IBLR_ML

public IBLR_ML()

Default constructor uses 10 NN

IBLR_ML

public IBLR_ML(int numNeighbors)

Constructor that sets the number of neighbors

Parameters:

numNeighbors - the number of nearest neighbors considered

IBLR_ML

public IBLR_ML(int numNeighbors,
               boolean addFeatures)

Full constructor

Parameters:

numNeighbors - the number of nearest neighbors considered

addFeatures - when true, IBLR-ML+ is used

Method Detail

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

buildInternal

protected void buildInternal(MultiLabelInstances mltrain)
                      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.

Overrides:

buildInternal in class MultiLabelKNN

Parameters:

mltrain - the training data set

Throws:

Exception - if learner model was not created successfully

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

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