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: 8034 $

Author:

Len Trigg (trigg@cs.waikato.ac.nz)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static String	STEP_FIELD_NAME The name of the key field containing the learning rate step number

Constructor Summary

Constructors

Constructor and Description
LearningRateResultProducer()

Method Summary

Methods

Modifier and Type	Method and Description
void	acceptResult(ResultProducer rp, Object[] key, Object[] result) Accepts results from a ResultProducer.
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.
Enumeration	enumerateMeasures() Returns an enumeration of any additional measure names that might be in the result producer
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).
String[]	getKeyNames() Gets the names of each of the columns produced for a single run.
Object[]	getKeyTypes() Gets the data types of each of the columns produced for a single run.
int	getLowerSize() Get the value of LowerSize.
double	getMeasure(String additionalMeasureName) Returns the value of the named measure
String[]	getOptions() Gets the current settings of the result producer.
String[]	getResultNames() Gets the names of each of the columns produced for a single run.
ResultProducer	getResultProducer() Get the ResultProducer.
Object[]	getResultTypes() Gets the data types of each of the columns produced for a single run.
String	getRevision() Returns the revision string.
int	getStepSize() Get the value of StepSize.
int	getUpperSize() Get the value of UpperSize.
String	globalInfo() Returns a string describing this result producer
boolean	isResultRequired(ResultProducer rp, Object[] key) Determines whether the results for a specified key must be generated.
Enumeration	listOptions() Returns an enumeration describing the available options..
String	lowerSizeTipText() Returns the tip text for this property
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.
String	resultProducerTipText() Returns the tip text for this property
void	setAdditionalMeasures(String[] additionalMeasures) Set a list of method names for additional measures to look for in SplitEvaluators.
void	setInstances(Instances instances) Sets the dataset that results will be obtained for.
void	setLowerSize(int newLowerSize) Set the value of LowerSize.
void	setOptions(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.
void	setStepSize(int newStepSize) Set the value of StepSize.
void	setUpperSize(int newUpperSize) Set the value of UpperSize.
String	stepSizeTipText() Returns the tip text for this property
String	toString() Gets a text descrption of the result producer.
String	upperSizeTipText() Returns the tip text for this property

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

STEP_FIELD_NAME

public static String STEP_FIELD_NAME

The name of the key field containing the learning rate step number

Constructor Detail

LearningRateResultProducer

public LearningRateResultProducer()

Method Detail

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 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 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