Constructor Detail

• ClassifierSplitEvaluator

  public ClassifierSplitEvaluator()

  No args constructor.

Method Detail

• globalInfo

  public java.lang.String globalInfo()

  Returns a string describing this split evaluator

  Returns:

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

• 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:

   -W <class name>
    The full class name of the classifier.
    eg: weka.classifiers.bayes.NaiveBayes
   

   -C <index>
    The index of the class for which IR statistics
    are to be output. (default 1)
   

   -I <index>
    The index of an attribute to output in the
    results. This attribute should identify an
    instance in order to know which instances are
    in the test set of a cross validation. if 0
    no output (default 0).
   

   -P
    Add target and prediction columns to the result
    for each fold.
   

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

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

  All options after -- will be passed to the classifier.

  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 Classifier.

  Specified by:

  getOptions in interface OptionHandler

  Returns:

  an array of strings suitable for passing to setOptions

• setAdditionalMeasures

  public void setAdditionalMeasures​(java.lang.String[] additionalMeasures)

  Set a list of method names for additional measures to look for in Classifiers. This could contain many measures (of which only a subset may be produceable by the current Classifier) if an experiment is the type that iterates over a set of properties.

  Specified by:

  setAdditionalMeasures in interface SplitEvaluator

  Parameters:

  additionalMeasures - a list of method names

• enumerateMeasures

  public java.util.Enumeration enumerateMeasures()

  Returns an enumeration of any additional measure names that might be in the classifier

  Specified by:

  enumerateMeasures in interface AdditionalMeasureProducer

  Returns:

  an enumeration of the measure names

• getMeasure

  public double getMeasure​(java.lang.String additionalMeasureName)

  Returns the value of the named measure

  Specified by:

  getMeasure in interface AdditionalMeasureProducer

  Parameters:

  additionalMeasureName - the name of the measure to query for its value

  Returns:

  the value of the named measure

  Throws:

  java.lang.IllegalArgumentException - if the named measure is not supported

• getKeyTypes

  public java.lang.Object[] getKeyTypes()

  Gets the data types of each of the key columns produced for a single run. The number of key fields must be constant for a given SplitEvaluator.

  Specified by:

  getKeyTypes in interface SplitEvaluator

  Returns:

  an array containing objects of the type of each key column. The objects should be Strings, or Doubles.

• getKeyNames

  public java.lang.String[] getKeyNames()

  Gets the names of each of the key columns produced for a single run. The number of key fields must be constant for a given SplitEvaluator.

  Specified by:

  getKeyNames in interface SplitEvaluator

  Returns:

  an array containing the name of each key column

• getKey

  public java.lang.Object[] getKey()

  Gets the key describing the current SplitEvaluator. For example This may contain the name of the classifier used for classifier predictive evaluation. The number of key fields must be constant for a given SplitEvaluator.

  Specified by:

  getKey in interface SplitEvaluator

  Returns:

  an array of objects containing the key.

• getResultTypes

  public java.lang.Object[] getResultTypes()

  Gets the data types of each of the result columns produced for a single run. The number of result fields must be constant for a given SplitEvaluator.

  Specified by:

  getResultTypes in interface SplitEvaluator

  Returns:

  an array containing objects of the type of each result column. The objects should be Strings, or Doubles.

• getResultNames

  public java.lang.String[] getResultNames()

  Gets the names of each of the result columns produced for a single run. The number of result fields must be constant for a given SplitEvaluator.

  Specified by:

  getResultNames in interface SplitEvaluator

  Returns:

  an array containing the name of each result column

• getResult

  public java.lang.Object[] getResult​(Instances train,
                                      Instances test)
                               throws java.lang.Exception

  Gets the results for the supplied train and test datasets. Now performs a deep copy of the classifier before it is built and evaluated (just in case the classifier is not initialized properly in buildClassifier()).

  Specified by:

  getResult in interface SplitEvaluator

  Parameters:

  train - the training Instances.

  test - the testing Instances.

  Returns:

  the results stored in an array. The objects stored in the array may be Strings, Doubles, or null (for the missing value).

  Throws:

  java.lang.Exception - if a problem occurs while getting the results

• classifierTipText

  public java.lang.String classifierTipText()

  Returns the tip text for this property

  Returns:

  tip text for this property suitable for displaying in the explorer/experimenter gui

• getClassifier

  public Classifier getClassifier()

  Get the value of Classifier.

  Returns:

  Value of Classifier.

• setClassifier

  public void setClassifier​(Classifier newClassifier)

  Sets the classifier.

  Parameters:

  newClassifier - the new classifier to use.

• getClassForIRStatistics

  public int getClassForIRStatistics()

  Get the value of ClassForIRStatistics.

  Returns:

  Value of ClassForIRStatistics.

• setClassForIRStatistics

  public void setClassForIRStatistics​(int v)

  Set the value of ClassForIRStatistics.

  Parameters:

  v - Value to assign to ClassForIRStatistics.

• getAttributeID

  public int getAttributeID()

  Get the index of Attibute Identifying the instances

  Returns:

  index of outputed Attribute.

• setAttributeID

  public void setAttributeID​(int v)

  Set the index of Attibute Identifying the instances

  Parameters:

  v - index the attribute to output

• getPredTargetColumn

  public boolean getPredTargetColumn()

  Returns:

  true if the prediction and target columns must be outputed.

• setPredTargetColumn

  public void setPredTargetColumn​(boolean v)

  Set the flag for prediction and target output.

  Parameters:

  v - true if the 2 columns have to be outputed. false otherwise.

• setClassifierName

  public void setClassifierName​(java.lang.String newClassifierName)
                         throws java.lang.Exception

  Set the Classifier to use, given it's class name. A new classifier will be instantiated.

  Parameters:

  newClassifierName - the Classifier class name.

  Throws:

  java.lang.Exception - if the class name is invalid.

• getRawResultOutput

  public java.lang.String getRawResultOutput()

  Gets the raw output from the classifier

  Specified by:

  getRawResultOutput in interface SplitEvaluator

  Returns:

  the raw output from th,0e classifier

• toString

  public java.lang.String toString()

  Returns a text description of the split evaluator.

  Overrides:

  toString in class java.lang.Object

  Returns:

  a text description of the split evaluator.

• getRevision

  public java.lang.String getRevision()

  Returns the revision string.

  Specified by:

  getRevision in interface RevisionHandler

  Returns:

  the revision