Package weka.experiment

Class LearningRateResultProducer

java.lang.Object
weka.experiment.LearningRateResultProducer
All Implemented Interfaces:
Serializable, AdditionalMeasureProducer, OptionHandler, RevisionHandler, ResultListener, ResultProducer
public class LearningRateResultProducer extends Object implements ResultListener, ResultProducer, OptionHandler, AdditionalMeasureProducer, RevisionHandler
Tells a sub-ResultProducer to reproduce the current run for varying sized subsamples of the dataset. Normally used with an AveragingResultProducer and CrossValidationResultProducer combo to generate learning curve results. For non-numeric result fields, the first value is used.

Valid options are: 

 -X <num steps>
  The number of steps in the learning rate curve.
  (default 10)
 
 -W <class name>
  The full class name of a ResultProducer.
  eg: weka.experiment.CrossValidationResultProducer
 
 Options specific to result producer weka.experiment.AveragingResultProducer:
 
 -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: 10203 $
Author:
Len Trigg (trigg@cs.waikato.ac.nz)
See Also:

  • Field Details

    • STEP_FIELD_NAME

      public static String STEP_FIELD_NAME
      The name of the key field containing the learning rate step number

  • Constructor Details

    • LearningRateResultProducer

      public LearningRateResultProducer()

  • Method Details

    • globalInfo

      public 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 String[] determineColumnConstraints(ResultProducer rp) throws 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:
      Exception - if constraints can't be determined

    • doRunKeys

      public void doRunKeys(int run) throws 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:
      Exception - if a problem occurs while getting the keys

    • doRun

      public void doRun(int run) throws 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:
      Exception - if a problem occurs while getting the results

    • preProcess

      public void preProcess(ResultProducer rp) throws Exception
      Prepare for the results to be received.
      Specified by:
      preProcess in interface ResultListener
      Parameters:
      rp - the ResultProducer that will generate the results
      Throws:
      Exception - if an error occurs during preprocessing.

    • preProcess

      public void preProcess() throws 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:
      Exception - if an error occurs during preprocessing.

    • postProcess

      public void postProcess(ResultProducer rp) throws 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:
      Exception - if an error occurs

    • postProcess

      public void postProcess() throws 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:
      Exception - if an error occurs

    • acceptResult

      public void acceptResult(ResultProducer rp, Object[] key, Object[] result) throws 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:
      Exception - if the result could not be accepted.

    • isResultRequired

      public boolean isResultRequired(ResultProducer rp, Object[] key) throws 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:
      Exception - if it could not be determined if the result is needed.

    • getKeyNames

      public String[] getKeyNames() throws 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:
      Exception - if key names cannot be generated

    • getKeyTypes

      public Object[] getKeyTypes() throws 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:
      Exception - if the key types could not be determined (perhaps because of a problem from a nested sub-resultproducer)

    • getResultNames

      public String[] getResultNames() throws 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:
      Exception - if the result names could not be determined (perhaps because of a problem from a nested sub-resultproducer)

    • getResultTypes

      public Object[] getResultTypes() throws 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:
      Exception - if the result types could not be determined (perhaps because of a problem from a nested sub-resultproducer)

    • getCompatibilityState

      public 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 Enumeration<Option> 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(String[] options) throws Exception
      Parses a given list of options.

      Valid options are: 

       -X <num steps>
  The number of steps in the learning rate curve.
  (default 10)
 
       -W <class name>
  The full class name of a ResultProducer.
  eg: weka.experiment.CrossValidationResultProducer
 
       Options specific to result producer weka.experiment.AveragingResultProducer:
 
       -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:
      Exception - if an option is not supported

    • getOptions

      public 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(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 Enumeration<String> 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(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:
      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'.

    • lowerSizeTipText

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

    • getLowerSize

      public int getLowerSize()
      Get the value of LowerSize.
      Returns:
      Value of LowerSize.

    • setLowerSize

      public void setLowerSize(int newLowerSize)
      Set the value of LowerSize.
      Parameters:
      newLowerSize - Value to assign to LowerSize.

    • upperSizeTipText

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

    • getUpperSize

      public int getUpperSize()
      Get the value of UpperSize.
      Returns:
      Value of UpperSize.

    • setUpperSize

      public void setUpperSize(int newUpperSize)
      Set the value of UpperSize.
      Parameters:
      newUpperSize - Value to assign to UpperSize.

    • stepSizeTipText

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

    • getStepSize

      public int getStepSize()
      Get the value of StepSize.
      Returns:
      Value of StepSize.

    • setStepSize

      public void setStepSize(int newStepSize)
      Set the value of StepSize.
      Parameters:
      newStepSize - Value to assign to StepSize.

    • 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 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 String toString()
      Gets a text descrption of the result producer.
      Overrides:
      toString in class Object
      Returns:
      a text description of the result producer.

    • getRevision

      public String getRevision()
      Returns the revision string.
      Specified by:
      getRevision in interface RevisionHandler
      Returns:
      the revision