AveragingResultProducer

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## weka.experiment
Class AveragingResultProducer

    java.lang.Object
      weka.experiment.AveragingResultProducer

All Implemented Interfaces:
  java.io.Serializable, AdditionalMeasureProducer, OptionHandler, RevisionHandler, ResultListener, ResultProducer

    public class AveragingResultProducer

extends java.lang.Object
implements ResultListener, ResultProducer, OptionHandler, AdditionalMeasureProducer, RevisionHandler

Takes the results from a ResultProducer and submits the average to the result listener. Normally used with a CrossValidationResultProducer to perform n x m fold cross validation. For non-numeric result fields, the first value is used.

Valid options are:

     -F <field name>
      The name of the field to average over.
      (default "Fold")

     -X <num results>
      The number of results expected per average.
      (default 10)

     -S
      Calculate standard deviations.
      (default only averages)

     -W <class name>
      The full class name of a ResultProducer.
      eg: weka.experiment.CrossValidationResultProducer

     Options specific to result producer weka.experiment.CrossValidationResultProducer:

     -X <number of folds>
      The number of folds to use for the cross-validation.
      (default 10)

     -D
     Save raw split evaluator output.

     -O <file/directory name/path>
      The filename where raw output will be stored.
      If a directory name is specified then then individual
      outputs will be gzipped, otherwise all output will be
      zipped to the named file. Use in conjuction with -D. (default splitEvalutorOut.zip)

     -W <class name>
      The full class name of a SplitEvaluator.
      eg: weka.experiment.ClassifierSplitEvaluator

     Options specific to split evaluator weka.experiment.ClassifierSplitEvaluator:

     -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 result producer.

Version:
  $Revision: 1.18 $
Author:
  Len Trigg (trigg@cs.waikato.ac.nz)
See Also:
  Serialized Form

Constructor Summary
`AveragingResultProducer()`

Method Summary
`void` | `acceptResult(ResultProducer rp, java.lang.Object[] key, java.lang.Object[] result)` Accepts results from a ResultProducer.
`java.lang.String` | `calculateStdDevsTipText()` Returns the tip text for this property
`java.lang.String[]` | `determineColumnConstraints(ResultProducer rp)` Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
`void` | `doRun(int run)` Gets the results for a specified run number.
`void` | `doRunKeys(int run)` Gets the keys for a specified run number.
`java.util.Enumeration` | `enumerateMeasures()` Returns an enumeration of any additional measure names that might be in the result producer
`java.lang.String` | `expectedResultsPerAverageTipText()` Returns the tip text for this property
`boolean` | `getCalculateStdDevs()` Get the value of CalculateStdDevs.
`java.lang.String` | `getCompatibilityState()` Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
`int` | `getExpectedResultsPerAverage()` Get the value of ExpectedResultsPerAverage.
`java.lang.String` | `getKeyFieldName()` Get the value of KeyFieldName.
`java.lang.String[]` | `getKeyNames()` Gets the names of each of the columns produced for a single run.
`java.lang.Object[]` | `getKeyTypes()` Gets the data types of each of the columns produced for a single run.
`double` | `getMeasure(java.lang.String additionalMeasureName)` Returns the value of the named measure
`java.lang.String[]` | `getOptions()` Gets the current settings of the result producer.
`java.lang.String[]` | `getResultNames()` Gets the names of each of the columns produced for a single run.
`ResultProducer` | `getResultProducer()` Get the ResultProducer.
`java.lang.Object[]` | `getResultTypes()` Gets the data types of each of the columns produced for a single run.
`java.lang.String` | `getRevision()` Returns the revision string.
`java.lang.String` | `globalInfo()` Returns a string describing this result producer
`boolean` | `isResultRequired(ResultProducer rp, java.lang.Object[] key)` Determines whether the results for a specified key must be generated.
`java.lang.String` | `keyFieldNameTipText()` Returns the tip text for this property
`java.util.Enumeration` | `listOptions()` Returns an enumeration describing the available options..
`void` | `postProcess()` When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.
`void` | `postProcess(ResultProducer rp)` When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.
`void` | `preProcess()` Prepare to generate results.
`void` | `preProcess(ResultProducer rp)` Prepare for the results to be received.
`java.lang.String` | `resultProducerTipText()` Returns the tip text for this property
`void` | `setAdditionalMeasures(java.lang.String[] additionalMeasures)` Set a list of method names for additional measures to look for in SplitEvaluators.
`void` | `setCalculateStdDevs(boolean newCalculateStdDevs)` Set the value of CalculateStdDevs.
`void` | `setExpectedResultsPerAverage(int newExpectedResultsPerAverage)` Set the value of ExpectedResultsPerAverage.
`void` | `setInstances(Instances instances)` Sets the dataset that results will be obtained for.
`void` | `setKeyFieldName(java.lang.String newKeyFieldName)` Set the value of KeyFieldName.
`void` | `setOptions(java.lang.String[] options)` Parses a given list of options.
`void` | `setResultListener(ResultListener listener)` Sets the object to send results of each run to.
`void` | `setResultProducer(ResultProducer newResultProducer)` Set the ResultProducer.
`java.lang.String` | `toString()` Gets a text descrption of the result producer.

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, wait, wait, wait`

Constructor Detail

### AveragingResultProducer

    public AveragingResultProducer()

Method Detail

### globalInfo

    public java.lang.String globalInfo()

  Returns a string describing this result producer

  Returns:
    a description of the result producer suitable for displaying in the explorer/experimenter gui

### determineColumnConstraints

    public java.lang.String[] determineColumnConstraints(ResultProducer rp)
                                                  throws java.lang.Exception

  Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers. Null should be returned if there are NO constraints, otherwise a list of column names should be returned as an array of Strings.

  Specified by:
    `determineColumnConstraints` in interface `ResultListener`
  Parameters:
    `rp` - the ResultProducer to which the constraints will apply
  Returns:
    an array of column names to which resutltProducer's results will be restricted.
  Throws:
    `java.lang.Exception` - if constraints can't be determined

### doRunKeys

    public void doRunKeys(int run)
                   throws java.lang.Exception

  Gets the keys for a specified run number. Different run numbers correspond to different randomizations of the data. Keys produced should be sent to the current ResultListener

  Specified by:
    `doRunKeys` in interface `ResultProducer`
  Parameters:
    `run` - the run number to get keys for.
  Throws:
    `java.lang.Exception` - if a problem occurs while getting the keys

### doRun

    public void doRun(int run)
               throws java.lang.Exception

  Gets the results for a specified run number. Different run numbers correspond to different randomizations of the data. Results produced should be sent to the current ResultListener

  Specified by:
    `doRun` in interface `ResultProducer`
  Parameters:
    `run` - the run number to get results for.
  Throws:
    `java.lang.Exception` - if a problem occurs while getting the results

### preProcess

    public void preProcess(ResultProducer rp)
                    throws java.lang.Exception

  Prepare for the results to be received.

  Specified by:
    `preProcess` in interface `ResultListener`
  Parameters:
    `rp` - the ResultProducer that will generate the results
  Throws:
    `java.lang.Exception` - if an error occurs during preprocessing.

### preProcess

    public void preProcess()
                    throws java.lang.Exception

  Prepare to generate results. The ResultProducer should call preProcess(this) on the ResultListener it is to send results to.

  Specified by:
    `preProcess` in interface `ResultProducer`
  Throws:
    `java.lang.Exception` - if an error occurs during preprocessing.

### postProcess

    public void postProcess(ResultProducer rp)
                     throws java.lang.Exception

  When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.

  Specified by:
    `postProcess` in interface `ResultListener`
  Parameters:
    `rp` - the ResultProducer that generated the results
  Throws:
    `java.lang.Exception` - if an error occurs

### postProcess

    public void postProcess()
                     throws java.lang.Exception

  When this method is called, it indicates that no more requests to generate results for the current experiment will be sent. The ResultProducer should call preProcess(this) on the ResultListener it is to send results to.

  Specified by:
    `postProcess` in interface `ResultProducer`
  Throws:
    `java.lang.Exception` - if an error occurs

### acceptResult

    public void acceptResult(ResultProducer rp,
                             java.lang.Object[] key,
                             java.lang.Object[] result)
                      throws java.lang.Exception

  Accepts results from a ResultProducer.

  Specified by:
    `acceptResult` in interface `ResultListener`
  Parameters:
    `rp` - the ResultProducer that generated the results
    `key` - an array of Objects (Strings or Doubles) that uniquely identify a result for a given ResultProducer with given compatibilityState
    `result` - 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 the result could not be accepted.

### isResultRequired

    public boolean isResultRequired(ResultProducer rp,
                                    java.lang.Object[] key)
                             throws java.lang.Exception

  Determines whether the results for a specified key must be generated.

  Specified by:
    `isResultRequired` in interface `ResultListener`
  Parameters:
    `rp` - the ResultProducer wanting to generate the results
    `key` - an array of Objects (Strings or Doubles) that uniquely identify a result for a given ResultProducer with given compatibilityState
  Returns:
    true if the result should be generated
  Throws:
    `java.lang.Exception` - if it could not be determined if the result is needed.

### getKeyNames

    public java.lang.String[] getKeyNames()
                                   throws java.lang.Exception

  Gets the names of each of the columns produced for a single run.

  Specified by:
    `getKeyNames` in interface `ResultProducer`
  Returns:
    an array containing the name of each column
  Throws:
    `java.lang.Exception` - if key names cannot be generated

### getKeyTypes

    public java.lang.Object[] getKeyTypes()
                                   throws java.lang.Exception

  Gets the data types of each of the columns produced for a single run. This method should really be static.

  Specified by:
    `getKeyTypes` in interface `ResultProducer`
  Returns:
    an array containing objects of the type of each column. The objects should be Strings, or Doubles.
  Throws:
    `java.lang.Exception` - if the key types could not be determined (perhaps because of a problem from a nested sub-resultproducer)

### getResultNames

    public java.lang.String[] getResultNames()
                                      throws java.lang.Exception

  Gets the names of each of the columns produced for a single run. A new result field is added for the number of results used to produce each average. If only averages are being produced the names are not altered, if standard deviations are produced then "Dev_" and "Avg_" are prepended to each result deviation and average field respectively.

  Specified by:
    `getResultNames` in interface `ResultProducer`
  Returns:
    an array containing the name of each column
  Throws:
    `java.lang.Exception` - if the result names could not be determined (perhaps because of a problem from a nested sub-resultproducer)

### getResultTypes

    public java.lang.Object[] getResultTypes()
                                      throws java.lang.Exception

  Gets the data types of each of the columns produced for a single run.

  Specified by:
    `getResultTypes` in interface `ResultProducer`
  Returns:
    an array containing objects of the type of each column. The objects should be Strings, or Doubles.
  Throws:
    `java.lang.Exception` - if the result types could not be determined (perhaps because of a problem from a nested sub-resultproducer)

### getCompatibilityState

    public java.lang.String getCompatibilityState()

  Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface). For example, a cross-validation ResultProducer may have a setting for the number of folds. For a given state, the results produced should be compatible. Typically if a ResultProducer is an OptionHandler, this string will represent the command line arguments required to set the ResultProducer to that state.

  Specified by:
    `getCompatibilityState` in interface `ResultProducer`
  Returns:
    the description of the ResultProducer state, or null if no state is defined

### 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:

       -F <field name>
        The name of the field to average over.
        (default "Fold")

       -X <num results>
        The number of results expected per average.
        (default 10)

       -S
        Calculate standard deviations.
        (default only averages)

       -W <class name>
        The full class name of a ResultProducer.
        eg: weka.experiment.CrossValidationResultProducer

       Options specific to result producer weka.experiment.CrossValidationResultProducer:

       -X <number of folds>
        The number of folds to use for the cross-validation.
        (default 10)

       -D
       Save raw split evaluator output.

       -O <file/directory name/path>
        The filename where raw output will be stored.
        If a directory name is specified then then individual
        outputs will be gzipped, otherwise all output will be
        zipped to the named file. Use in conjuction with -D. (default splitEvalutorOut.zip)

       -W <class name>
        The full class name of a SplitEvaluator.
        eg: weka.experiment.ClassifierSplitEvaluator

       Options specific to split evaluator weka.experiment.ClassifierSplitEvaluator:

       -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 result producer.

  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 result producer.

  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 SplitEvaluators. This could contain many measures (of which only a subset may be produceable by the current resultProducer) if an experiment is the type that iterates over a set of properties.

  Specified by:
    `setAdditionalMeasures` in interface `ResultProducer`
  Parameters:
    `additionalMeasures` - an array of measure names, null if none

### enumerateMeasures

    public java.util.Enumeration enumerateMeasures()

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

  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

### setInstances

    public void setInstances(Instances instances)

  Sets the dataset that results will be obtained for.

  Specified by:
    `setInstances` in interface `ResultProducer`
  Parameters:
    `instances` - a value of type 'Instances'.

### calculateStdDevsTipText

    public java.lang.String calculateStdDevsTipText()

  Returns the tip text for this property

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

### getCalculateStdDevs

    public boolean getCalculateStdDevs()

  Get the value of CalculateStdDevs.

  Returns:
    Value of CalculateStdDevs.

### setCalculateStdDevs

    public void setCalculateStdDevs(boolean newCalculateStdDevs)

  Set the value of CalculateStdDevs.

  Parameters:
    `newCalculateStdDevs` - Value to assign to CalculateStdDevs.

### expectedResultsPerAverageTipText

    public java.lang.String expectedResultsPerAverageTipText()

  Returns the tip text for this property

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

### getExpectedResultsPerAverage

    public int getExpectedResultsPerAverage()

  Get the value of ExpectedResultsPerAverage.

  Returns:
    Value of ExpectedResultsPerAverage.

### setExpectedResultsPerAverage

    public void setExpectedResultsPerAverage(int newExpectedResultsPerAverage)

  Set the value of ExpectedResultsPerAverage.

  Parameters:
    `newExpectedResultsPerAverage` - Value to assign to ExpectedResultsPerAverage.

### keyFieldNameTipText

    public java.lang.String keyFieldNameTipText()

  Returns the tip text for this property

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

### getKeyFieldName

    public java.lang.String getKeyFieldName()

  Get the value of KeyFieldName.

  Returns:
    Value of KeyFieldName.

### setKeyFieldName

    public void setKeyFieldName(java.lang.String newKeyFieldName)

  Set the value of KeyFieldName.

  Parameters:
    `newKeyFieldName` - Value to assign to KeyFieldName.

### setResultListener

    public void setResultListener(ResultListener listener)

  Sets the object to send results of each run to.

  Specified by:
    `setResultListener` in interface `ResultProducer`
  Parameters:
    `listener` - a value of type 'ResultListener'

### resultProducerTipText

    public java.lang.String resultProducerTipText()

  Returns the tip text for this property

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

### getResultProducer

    public ResultProducer getResultProducer()

  Get the ResultProducer.

  Returns:
    the ResultProducer.

### setResultProducer

    public void setResultProducer(ResultProducer newResultProducer)

  Set the ResultProducer.

  Parameters:
    `newResultProducer` - new ResultProducer to use.

### toString

    public java.lang.String toString()

  Gets a text descrption of the result producer.

  Overrides:
    `toString` in class `java.lang.Object`
  Returns:
    a text description of the result producer.

### getRevision

    public java.lang.String getRevision()

  Returns the revision string.

  Specified by:
    `getRevision` in interface `RevisionHandler`
  Returns:
    the revision

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