Package weka.classifiers.lazy

Class LWLSynchro

  • All Implemented Interfaces:
    adams.core.Stoppable, adams.core.StoppableWithFeedback, Serializable, Cloneable, weka.classifiers.Classifier, ThreadSafeClassifier, weka.classifiers.UpdateableClassifier, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.OptionHandler, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler, weka.core.WeightedInstancesHandler
    Direct Known Subclasses:
    AbstainingLWL, LWLIntervalEstimator
    public class LWLSynchro
extends weka.classifiers.lazy.LWL
implements ThreadSafeClassifier, adams.core.StoppableWithFeedback
    Locally weighted learning. Uses an instance-based algorithm to assign instance weights which are then used by a specified WeightedInstancesHandler.
    Can do classification (e.g. using naive Bayes) or regression (e.g. using linear regression).

    For more info, see

    Eibe Frank, Mark Hall, Bernhard Pfahringer: Locally Weighted Naive Bayes. In: 19th Conference in Uncertainty in Artificial Intelligence, 249-256, 2003.

    C. Atkeson, A. Moore, S. Schaal (1996). Locally weighted learning. AI Review..

    BibTeX: 
     @inproceedings{Frank2003,
    author = {Eibe Frank and Mark Hall and Bernhard Pfahringer},
    booktitle = {19th Conference in Uncertainty in Artificial Intelligence},
    pages = {249-256},
    publisher = {Morgan Kaufmann},
    title = {Locally Weighted Naive Bayes},
    year = {2003}
 }

 @article{Atkeson1996,
    author = {C. Atkeson and A. Moore and S. Schaal},
    journal = {AI Review},
    title = {Locally weighted learning},
    year = {1996}
 }


    Valid options are: 

     -no-update
  Suppresses the update of the nearest neighbor search (nns)
  algorithm with the data that is to be classified.
 (default: nns gets updated).
 
     -A
  The nearest neighbour search algorithm to use (default: weka.core.neighboursearch.LinearNNSearch).
 
     -K <number of neighbours>
  Set the number of neighbours used to set the kernel bandwidth.
  (default all)
     -U <number of weighting method>
  Set the weighting kernel shape to use. 0=Linear, 1=Epanechnikov,
  2=Tricube, 3=Inverse, 4=Gaussian.
  (default 0 = Linear)
     -D
  If set, classifier is run in debug mode and
  may output additional info to the console
     -W
  Full name of base classifier.
  (default: weka.classifiers.functions.GaussianProcesses)
     Options specific to classifier weka.classifiers.functions.GaussianProcesses:
 
     -D
  If set, classifier is run in debug mode and
  may output additional info to the console
     -L <double>
  Level of Gaussian Noise wrt transformed target. (default 1)
     -N
  Whether to 0=normalize/1=standardize/2=neither. (default 0=normalize)
     -K <classname and parameters>
  The Kernel to use.
  (default: weka.classifiers.functions.supportVector.PolyKernel)
     Options specific to kernel weka.classifiers.functions.supportVector.PolyKernel:
 
     -D
  Enables debugging output (if available) to be printed.
  (default: off)
     -no-checks
  Turns off all checks - use with caution!
  (default: checks on)
     -C <num>
  The size of the cache (a prime number), 0 for full cache and
  -1 to turn it off.
  (default: 250007)
     -E <num>
  The Exponent to use.
  (default: 1.0)
     -L
  Use lower-order terms.
  (default: no)
    Note: the build(Instance) needs manual syncing with the original WEKA classifier (distributionForInstance(Instance) method).
    Version:
    $Revision$
    Author:
    Len Trigg ([email protected]), Eibe Frank ([email protected]), Ashraf M. Kibriya (amk14[at-the-rate]cs[dot]waikato[dot]ac[dot]nz)
    See Also:
    LWL.distributionForInstance(Instance), Serialized Form

    • Field Summary

      Fields 
      Modifier and Type Field Description
      protected boolean m_NoUpdate
      whether to suppress the update of the nearest-neighbor search algorithm when making predictions.
      protected boolean m_Stopped
      whether the classifier was stopped.

      • Fields inherited from class weka.classifiers.lazy.LWL

        CONSTANT, EPANECHNIKOV, GAUSS, INVERSE, LINEAR, m_kNN, m_NNSearch, m_Train, m_UseAllK, m_WeightKernel, m_ZeroR, TRICUBE

      • Fields inherited from class weka.classifiers.SingleClassifierEnhancer

        m_Classifier

      • Fields inherited from class weka.classifiers.AbstractClassifier

        BATCH_SIZE_DEFAULT, m_BatchSize, m_Debug, m_DoNotCheckCapabilities, m_numDecimalPlaces, NUM_DECIMAL_PLACES_DEFAULT

    • Constructor Summary

      Constructors 
      Constructor Description
      LWLSynchro()
      Initializes the classifier.

    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      protected void build​(weka.core.Instance instance)
      Builds the classifier.
      void buildClassifier​(weka.core.Instances instances)  
      protected String defaultClassifierString()
      Default classifier classname.
      double[] distributionForInstance​(weka.core.Instance instance)
      Calculates the class membership probabilities for the given test instance.
      boolean getNoUpdate()
      Returns whether to suppress the update of the nearest-neighbor search algorithm when making predictions.
      String[] getOptions()
      Gets the current settings of the classifier.
      String getRevision()
      Returns the revision string.
      boolean isStopped()
      Whether the execution has been stopped.
      Enumeration listOptions()
      Returns an enumeration describing the available options.
      static void main​(String[] argv)
      Main method for testing this class.
      String noUpdateTipText()
      Returns the tip text for this property.
      void setNoUpdate​(boolean value)
      Sets whether to suppress updating the nearest-neighbor search algorithm when making predictions.
      void setOptions​(String[] options)
      Parses a given list of options.
      void stopExecution()
      Stops the execution.
      String toString()
      Returns a description of this classifier.

      • Methods inherited from class weka.classifiers.lazy.LWL

        enumerateMeasures, getCapabilities, getKNN, getMeasure, getNearestNeighbourSearchAlgorithm, getTechnicalInformation, getWeightingKernel, globalInfo, KNNTipText, nearestNeighbourSearchAlgorithmTipText, setKNN, setNearestNeighbourSearchAlgorithm, setWeightingKernel, updateClassifier, weightingKernelTipText

      • Methods inherited from class weka.classifiers.SingleClassifierEnhancer

        classifierTipText, defaultClassifierOptions, getClassifier, getClassifierSpec, postExecution, preExecution, setClassifier

      • Methods inherited from class weka.classifiers.AbstractClassifier

        batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

      • Methods inherited from interface weka.classifiers.Classifier

        classifyInstance, getCapabilities

    • Field Detail

      • m_NoUpdate

        protected boolean m_NoUpdate
        whether to suppress the update of the nearest-neighbor search algorithm when making predictions.

      • m_Stopped

        protected boolean m_Stopped
        whether the classifier was stopped.

    • Constructor Detail

      • LWLSynchro

        public LWLSynchro()
        Initializes the classifier.

    • Method Detail

      • defaultClassifierString

        protected String defaultClassifierString()
        Default classifier classname.
        Overrides:
        defaultClassifierString in class weka.classifiers.lazy.LWL
        Returns:
        the classname

      • listOptions

        public Enumeration listOptions()
        Returns an enumeration describing the available options.
        Specified by:
        listOptions in interface weka.core.OptionHandler
        Overrides:
        listOptions in class weka.classifiers.lazy.LWL
        Returns:
        an enumeration of all the available options.

      • setOptions

        public void setOptions​(String[] options)
                throws Exception
        Parses a given list of options.

        Valid options are: 

         -no-update
  Suppresses the update of the nearest neighbor search (nns)
  algorithm with the data that is to be classified.
 (default: nns gets updated).
 
         -A
  The nearest neighbour search algorithm to use (default: weka.core.neighboursearch.LinearNNSearch).
 
         -K <number of neighbours>
  Set the number of neighbours used to set the kernel bandwidth.
  (default all)
         -U <number of weighting method>
  Set the weighting kernel shape to use. 0=Linear, 1=Epanechnikov,
  2=Tricube, 3=Inverse, 4=Gaussian.
  (default 0 = Linear)
         -D
  If set, classifier is run in debug mode and
  may output additional info to the console
         -W
  Full name of base classifier.
  (default: weka.classifiers.functions.GaussianProcesses)
         Options specific to classifier weka.classifiers.functions.GaussianProcesses:
 
         -D
  If set, classifier is run in debug mode and
  may output additional info to the console
         -L <double>
  Level of Gaussian Noise wrt transformed target. (default 1)
         -N
  Whether to 0=normalize/1=standardize/2=neither. (default 0=normalize)
         -K <classname and parameters>
  The Kernel to use.
  (default: weka.classifiers.functions.supportVector.PolyKernel)
         Options specific to kernel weka.classifiers.functions.supportVector.PolyKernel:
 
         -D
  Enables debugging output (if available) to be printed.
  (default: off)
         -no-checks
  Turns off all checks - use with caution!
  (default: checks on)
         -C <num>
  The size of the cache (a prime number), 0 for full cache and
  -1 to turn it off.
  (default: 250007)
         -E <num>
  The Exponent to use.
  (default: 1.0)
         -L
  Use lower-order terms.
  (default: no)
        Specified by:
        setOptions in interface weka.core.OptionHandler
        Overrides:
        setOptions in class weka.classifiers.lazy.LWL
        Parameters:
        options - the list of options as an array of strings
        Throws:
        Exception - if an option is not supported

      • getOptions

        public String[] getOptions()
        Gets the current settings of the classifier.
        Specified by:
        getOptions in interface weka.core.OptionHandler
        Overrides:
        getOptions in class weka.classifiers.lazy.LWL
        Returns:
        an array of strings suitable for passing to setOptions

      • noUpdateTipText

        public String noUpdateTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the explorer/experimenter gui

      • setNoUpdate

        public void setNoUpdate​(boolean value)
        Sets whether to suppress updating the nearest-neighbor search algorithm when making predictions.
        Parameters:
        value - if true then no update happens.

      • getNoUpdate

        public boolean getNoUpdate()
        Returns whether to suppress the update of the nearest-neighbor search algorithm when making predictions.
        Returns:
        true if the update is suppressed

      • buildClassifier

        public void buildClassifier​(weka.core.Instances instances)
                     throws Exception
        Specified by:
        buildClassifier in interface weka.classifiers.Classifier
        Overrides:
        buildClassifier in class weka.classifiers.lazy.LWL
        Throws:
        Exception

      • build

        protected void build​(weka.core.Instance instance)
              throws Exception
        Builds the classifier.

        Note: needs manual syncing with the distributionForInstance method of the original WEKA classifier.
        Parameters:
        instance - the instance to make prediction for
        Throws:
        Exception - if build fails
        See Also:
        LWL.distributionForInstance(Instance)

      • distributionForInstance

        public double[] distributionForInstance​(weka.core.Instance instance)
                                 throws Exception
        Calculates the class membership probabilities for the given test instance.
        Specified by:
        distributionForInstance in interface weka.classifiers.Classifier
        Overrides:
        distributionForInstance in class weka.classifiers.lazy.LWL
        Parameters:
        instance - the instance to be classified
        Returns:
        predicted class probability distribution
        Throws:
        Exception - if distribution can't be computed successfully

      • toString

        public String toString()
        Returns a description of this classifier.
        Overrides:
        toString in class weka.classifiers.lazy.LWL
        Returns:
        a description of this classifier as a string.

      • stopExecution

        public void stopExecution()
        Stops the execution.
        Specified by:
        stopExecution in interface adams.core.Stoppable

      • isStopped

        public boolean isStopped()
        Whether the execution has been stopped.
        Specified by:
        isStopped in interface adams.core.StoppableWithFeedback
        Returns:
        true if stopped

      • getRevision

        public String getRevision()
        Returns the revision string.
        Specified by:
        getRevision in interface weka.core.RevisionHandler
        Overrides:
        getRevision in class weka.classifiers.lazy.LWL
        Returns:
        the revision

      • main

        public static void main​(String[] argv)
        Main method for testing this class.
        Parameters:
        argv - the options