mulan.classifier.lazy
Class MLkNN

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

All Implemented Interfaces:

Serializable, MultiLabelLearner, TechnicalInformationHandler

public class MLkNN
extends MultiLabelKNN

Class implementing the ML-kNN (Multi-Label k Nearest Neighbours) algorithm.

For more information, see

Min-Ling Zhang, Zhi-Hua Zhou (2007). ML-KNN: A lazy learning approach to multi-label learning. Pattern Recogn.. 40(7):2038--2048.

BibTeX:

 @article{Zhang2007,
    address = {New York, NY, USA},
    author = {Min-Ling Zhang and Zhi-Hua Zhou},
    journal = {Pattern Recogn.},
    number = {7},
    pages = {2038--2048},
    publisher = {Elsevier Science Inc.},
    title = {ML-KNN: A lazy learning approach to multi-label learning},
    volume = {40},
    year = {2007},
    ISSN = {0031-3203}
 }
 

Version:

2012.07.16

Author:

Eleftherios Spyromitros-Xioufis

See Also:

Serialized Form

Field Summary

protected double

smooth Smoothing parameter controlling the strength of uniform prior (Default value is set to 1 which yields the Laplace smoothing).

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

MLkNN()
The default constructor

MLkNN(int numOfNeighbors, double smooth)

Method Summary

protected void	buildInternal(MultiLabelInstances train) 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

Field Detail

smooth

protected double smooth

Smoothing parameter controlling the strength of uniform prior
(Default value is set to 1 which yields the Laplace smoothing).

Constructor Detail

MLkNN

public MLkNN(int numOfNeighbors,
             double smooth)

Parameters:

numOfNeighbors - : the number of neighbors

smooth - : the smoothing factor

MLkNN

public MLkNN()

The default constructor

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

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

buildInternal

protected void buildInternal(MultiLabelInstances train)
                      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:

train - 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