Constructor Detail

• BVDecompose

  public BVDecompose()

Method Detail

• globalInfo

  public java.lang.String globalInfo()

  Returns a string describing this object

  Returns:

  a description of the classifier suitable for displaying in the explorer/experimenter gui

• getTechnicalInformation

  public 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.

  Specified by:

  getTechnicalInformation in interface TechnicalInformationHandler

  Returns:

  the technical information about this class

• listOptions

  public java.util.Enumeration listOptions()

  Returns an enumeration describing the available options.

  Specified by:

  listOptions in interface OptionHandler

  Returns:

  an enumeration of all the available options.

• setOptions

  public void setOptions​(java.lang.String[] options)
                  throws java.lang.Exception

  Parses a given list of options.

  Valid options are:

   -c <class index>
    The index of the class attribute.
    (default last)

   -t <name of arff file>
    The name of the arff file used for the decomposition.

   -T <training pool size>
    The number of instances placed in the training pool.
    The remainder will be used for testing. (default 100)

   -s <seed>
    The random number seed used.

   -x <num>
    The number of training repetitions used.
    (default 50)

   -D
    Turn on debugging output.

   -W <classifier class name>
    Full class name of the learner used in the decomposition.
    eg: weka.classifiers.bayes.NaiveBayes

   
   Options specific to learner weka.classifiers.rules.ZeroR:
   

   -D
    If set, classifier is run in debug mode and
    may output additional info to the console

  Options after -- are passed to the designated sub-learner.

  Specified by:

  setOptions in interface OptionHandler

  Parameters:

  options - the list of options as an array of strings

  Throws:

  java.lang.Exception - if an option is not supported

• getOptions

  public java.lang.String[] getOptions()

  Gets the current settings of the CheckClassifier.

  Specified by:

  getOptions in interface OptionHandler

  Returns:

  an array of strings suitable for passing to setOptions

• getTrainPoolSize

  public int getTrainPoolSize()

  Get the number of instances in the training pool.

  Returns:

  number of instances in the training pool.

• setTrainPoolSize

  public void setTrainPoolSize​(int numTrain)

  Set the number of instances in the training pool.

  Parameters:

  numTrain - number of instances in the training pool.

• setClassifier

  public void setClassifier​(Classifier newClassifier)

  Set the classifiers being analysed

  Parameters:

  newClassifier - the Classifier to use.

• getClassifier

  public Classifier getClassifier()

  Gets the name of the classifier being analysed

  Returns:

  the classifier being analysed.

• setDebug

  public void setDebug​(boolean debug)

  Sets debugging mode

  Parameters:

  debug - true if debug output should be printed

• getDebug

  public boolean getDebug()

  Gets whether debugging is turned on

  Returns:

  true if debugging output is on

• setSeed

  public void setSeed​(int seed)

  Sets the random number seed

  Parameters:

  seed - the random number seed

• getSeed

  public int getSeed()

  Gets the random number seed

  Returns:

  the random number seed

• setTrainIterations

  public void setTrainIterations​(int trainIterations)

  Sets the maximum number of boost iterations

  Parameters:

  trainIterations - the number of boost iterations

• getTrainIterations

  public int getTrainIterations()

  Gets the maximum number of boost iterations

  Returns:

  the maximum number of boost iterations

• setDataFileName

  public void setDataFileName​(java.lang.String dataFileName)

  Sets the name of the data file used for the decomposition

  Parameters:

  dataFileName - the data file to use

• getDataFileName

  public java.lang.String getDataFileName()

  Get the name of the data file used for the decomposition

  Returns:

  the name of the data file

• getClassIndex

  public int getClassIndex()

  Get the index (starting from 1) of the attribute used as the class.

  Returns:

  the index of the class attribute

• setClassIndex

  public void setClassIndex​(int classIndex)

  Sets index of attribute to discretize on

  Parameters:

  classIndex - the index (starting from 1) of the class attribute

• getBias

  public double getBias()

  Get the calculated bias squared

  Returns:

  the bias squared

• getVariance

  public double getVariance()

  Get the calculated variance

  Returns:

  the variance

• getSigma

  public double getSigma()

  Get the calculated sigma squared

  Returns:

  the sigma squared

• getError

  public double getError()

  Get the calculated error rate

  Returns:

  the error rate

• decompose

  public void decompose()
                 throws java.lang.Exception

  Carry out the bias-variance decomposition

  Throws:

  java.lang.Exception - if the decomposition couldn't be carried out

• toString

  public java.lang.String toString()

  Returns description of the bias-variance decomposition results.

  Overrides:

  toString in class java.lang.Object

  Returns:

  the bias-variance decomposition results as a string

• getRevision

  public java.lang.String getRevision()

  Returns the revision string.

  Specified by:

  getRevision in interface RevisionHandler

  Returns:

  the revision

• main

  public static void main​(java.lang.String[] args)

  Test method for this class

  Parameters:

  args - the command line arguments