adams.flow.sink
Class WekaExperimentGenerator

java.lang.Object
  adams.core.ConsoleObject
      adams.core.option.AbstractOptionHandler
          adams.flow.core.AbstractActor
              adams.flow.sink.AbstractSink
                  adams.flow.sink.WekaExperimentGenerator

All Implemented Interfaces:

AdditionalInformationHandler, CleanUpHandler, Debuggable, DebugOutputHandler, Destroyable, OptionHandler, QuickInfoSupporter, ShallowCopySupporter<AbstractActor>, SizeOfHandler, Stoppable, VariableChangeListener, ErrorHandler, InputConsumer, Serializable, Comparable

public class WekaExperimentGenerator
extends AbstractSink

Generates an experiment setup that can be used in conjunction with the Experiment transformer actor.

Input/output:
- accepts:
weka.classifiers.Classifier[]

Valid options are:

-D <int> (property: debugLevel)
    The greater the number the more additional info the scheme may output to
    the console (0 = off).
    default: 0
    minimum: 0
 

-name <java.lang.String> (property: name)
    The name of the actor.
    default: ExperimentGenerator
 

-annotation <adams.core.base.BaseText> (property: annotations)
    The annotations to attach to this actor.
    default:
 

-skip (property: skip)
    If set to true, transformation is skipped and the input token is just forwarded
    as it is.
 

-exp-type <CLASSIFICATION|REGRESSION> (property: experimentType)
    The type of experiment to perform.
    default: CLASSIFICATION
 

-eval-type <CROSS_VALIDATION|TRAIN_TEST_SPLIT_RANDOMIZED|TRAIN_TEST_SPLIT_ORDER_PRESERVED> (property: evaluationType)
    The type of evaluation to perform.
    default: CROSS_VALIDATION
 

-runs <int> (property: runs)
    The number of runs to perform.
    default: 10
    minimum: 1
 

-folds <int> (property: folds)
    The number of folds to use in cross-validation.
    default: 10
    minimum: 2
 

-split <double> (property: splitPercentage)
    The percentage to use in train/test splits.
    default: 66.0
    minimum: 1.0E-4
    maximum: 99.9999
 

-result-format <ARFF|CSV> (property: resultFormat)
    The data format the experimental results are stored in.
    default: ARFF
 

-result-file <adams.core.io.PlaceholderFile> (property: resultFile)
    The file to store the experimental results in.
    default: .
 

-output <adams.core.io.PlaceholderFile> (property: outputFile)
    The file to store the experiment setup in (the extension determines the
    type).
    default: .
 

Version:

$Revision: 4584 $

Author:

fracpete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Nested Class Summary

static class	WekaExperimentGenerator.EvaluationType The evaluation type.
static class	WekaExperimentGenerator.ExperimentType The experiment type.
static class	WekaExperimentGenerator.ResultFormat The data format the experiment data is stored in.

Field Summary

protected WekaExperimentGenerator.EvaluationType	m_EvaluationType the type of evaluation.
protected WekaExperimentGenerator.ExperimentType	m_ExperimentType the type of experiment.
protected int	m_Folds the number of folds to use (only cross-validation).
protected PlaceholderFile	m_OutputFile the file to store the experiment in.
protected PlaceholderFile	m_ResultFile the file to store the result in.
protected WekaExperimentGenerator.ResultFormat	m_ResultFormat the result format.
protected int	m_Runs the number of runs to perform.
protected double	m_SplitPercentage the split-percentage to use (only train/test splits).

Fields inherited from class adams.flow.sink.AbstractSink

BACKUP_INPUT, m_InputToken

Fields inherited from class adams.flow.core.AbstractActor

FILE_EXTENSION, FILE_EXTENSION_GZ, m_Annotations, m_BackupState, m_DetectedObjectVariables, m_DetectedVariables, m_ErrorHandler, m_Executed, m_FullName, m_Headless, m_Name, m_Parent, m_Root, m_Self, m_Skip, m_StopFlowOnError, m_StopMessage, m_Stopped, m_StorageHandler, m_VariablesUpdated

Fields inherited from class adams.core.option.AbstractOptionHandler

m_DebugLevel, m_OptionManager

Constructor Summary

WekaExperimentGenerator()

Method Summary

Class[]	accepts() Returns the class that the consumer accepts.
void	defineOptions() Adds options to the internal list of options.
protected String	doExecute() Executes the flow item.
String	evaluationTypeTipText() Returns the tip text for this property.
String	experimentTypeTipText() Returns the tip text for this property.
String	foldsTipText() Returns the tip text for this property.
WekaExperimentGenerator.EvaluationType	getEvaluationType() Returns the type of evaluation to perform.
WekaExperimentGenerator.ExperimentType	getExperimentType() Returns the type of experiment to perform.
int	getFolds() Returns the number of folds to use (only CV).
PlaceholderFile	getOutputFile() Returns the file to store the experiment in.
String	getQuickInfo() Returns a quick info about the actor, which will be displayed in the GUI.
PlaceholderFile	getResultFile() Returns the file to store the experimental results in.
WekaExperimentGenerator.ResultFormat	getResultFormat() Returns the data format the results are stored in.
int	getRuns() Returns the number of runs to perform.
double	getSplitPercentage() Returns the split percentage (only train/test splits).
String	globalInfo() Returns a string describing the object.
String	outputFileTipText() Returns the tip text for this property.
String	resultFileTipText() Returns the tip text for this property.
String	resultFormatTipText() Returns the tip text for this property.
String	runsTipText() Returns the tip text for this property.
void	setEvaluationType(WekaExperimentGenerator.EvaluationType value) Sets the type of evaluation to perform.
void	setExperimentType(WekaExperimentGenerator.ExperimentType value) Sets the type of experiment to perform.
void	setFolds(int value) Sets the number of folds to use (only CV).
void	setOutputFile(PlaceholderFile value) Sets the file to store the experiment setup in (the extensions determines the type).
void	setResultFile(PlaceholderFile value) Sets the file to store the experimental results in.
void	setResultFormat(WekaExperimentGenerator.ResultFormat value) Sets the data format the results are stored in.
void	setRuns(int value) Sets the number of runs to perform.
void	setSplitPercentage(double value) Sets the split percentage (only train/test splits).
String	setUp() Initializes the item for flow execution.
String	splitPercentageTipText() Returns the tip text for this property.

Methods inherited from class adams.flow.sink.AbstractSink

backupState, input, restoreState, wrapUp

Methods inherited from class adams.flow.core.AbstractActor

annotationsTipText, canInspectOptions, canPerformSetUpCheck, cleanUp, compareTo, debug, destroy, equals, execute, findVariables, findVariables, findVariables, forceVariables, forCommandLine, forName, getAdditionalInformation, getAnnotations, getDefaultName, getDetectedVariables, getErrorHandler, getFlowActors, getFullName, getName, getNextSibling, getParent, getPreviousSibling, getRoot, getSkip, getStopFlowOnError, getStopMessage, getStorageHandler, getVariables, handleError, hasErrorHandler, hasStopMessage, index, initialize, isBackedUp, isExecuted, isFinished, isHeadless, isStopped, nameTipText, performSetUpChecks, postExecute, preExecute, pruneBackup, pruneBackup, reset, setAnnotations, setErrorHandler, setHeadless, setName, setParent, setSkip, setStopFlowOnError, setVariables, shallowCopy, shallowCopy, sizeOf, skipTipText, stopExecution, stopExecution, stopFlowOnErrorTipText, updateDetectedVariables, updatePrefix, updateVariables, variableChanged

Methods inherited from class adams.core.option.AbstractOptionHandler

cleanUpOptions, debug, debugLevelTipText, finishInit, getDebugLevel, getOptionManager, isDebugOn, newOptionManager, setDebugLevel, toCommandLine, toString

Methods inherited from class adams.core.ConsoleObject

getDebugging, getSystemErr, getSystemOut

Methods inherited from class java.lang.Object

clone, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

m_ExperimentType

protected WekaExperimentGenerator.ExperimentType m_ExperimentType

the type of experiment.

m_EvaluationType

protected WekaExperimentGenerator.EvaluationType m_EvaluationType

the type of evaluation.

m_Runs

protected int m_Runs

the number of runs to perform.

m_Folds

protected int m_Folds

the number of folds to use (only cross-validation).

m_SplitPercentage

protected double m_SplitPercentage

the split-percentage to use (only train/test splits).

m_ResultFormat

protected WekaExperimentGenerator.ResultFormat m_ResultFormat

the result format.

m_ResultFile

protected PlaceholderFile m_ResultFile

the file to store the result in.

m_OutputFile

protected PlaceholderFile m_OutputFile

the file to store the experiment in.

Constructor Detail

WekaExperimentGenerator

public WekaExperimentGenerator()

Method Detail

globalInfo

public String globalInfo()

Returns a string describing the object.

Specified by:

globalInfo in class AbstractOptionHandler

Returns:

a description suitable for displaying in the gui

defineOptions

public void defineOptions()

Adds options to the internal list of options.

Specified by:

defineOptions in interface OptionHandler

Overrides:

defineOptions in class AbstractActor

getQuickInfo

public String getQuickInfo()

Returns a quick info about the actor, which will be displayed in the GUI.

Specified by:

getQuickInfo in interface QuickInfoSupporter

Overrides:

getQuickInfo in class AbstractActor

Returns:

null if no info available, otherwise short string

setExperimentType

public void setExperimentType(WekaExperimentGenerator.ExperimentType value)

Sets the type of experiment to perform.

Parameters:

value - the type

getExperimentType

public WekaExperimentGenerator.ExperimentType getExperimentType()

Returns the type of experiment to perform.

Returns:

the type

experimentTypeTipText

public String experimentTypeTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

setEvaluationType

public void setEvaluationType(WekaExperimentGenerator.EvaluationType value)

Sets the type of evaluation to perform.

Parameters:

value - the type

getEvaluationType

public WekaExperimentGenerator.EvaluationType getEvaluationType()

Returns the type of evaluation to perform.

Returns:

the type

evaluationTypeTipText

public String evaluationTypeTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

setRuns

public void setRuns(int value)

Sets the number of runs to perform.

Parameters:

value - the runs

getRuns

public int getRuns()

Returns the number of runs to perform.

Returns:

the runs

runsTipText

public String runsTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

setFolds

public void setFolds(int value)

Sets the number of folds to use (only CV).

Parameters:

value - the folds

getFolds

public int getFolds()

Returns the number of folds to use (only CV).

Returns:

the folds

foldsTipText

public String foldsTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

setSplitPercentage

public void setSplitPercentage(double value)

Sets the split percentage (only train/test splits).

Parameters:

value - the percentage (0-100)

getSplitPercentage

public double getSplitPercentage()

Returns the split percentage (only train/test splits).

Returns:

the data format

splitPercentageTipText

public String splitPercentageTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

setResultFormat

public void setResultFormat(WekaExperimentGenerator.ResultFormat value)

Sets the data format the results are stored in.

Parameters:

value - the format

getResultFormat

public WekaExperimentGenerator.ResultFormat getResultFormat()

Returns the data format the results are stored in.

Returns:

the format

resultFormatTipText

public String resultFormatTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

setResultFile

public void setResultFile(PlaceholderFile value)

Sets the file to store the experimental results in.

Parameters:

value - the file

getResultFile

public PlaceholderFile getResultFile()

Returns the file to store the experimental results in.

Returns:

the file

resultFileTipText

public String resultFileTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

setOutputFile

public void setOutputFile(PlaceholderFile value)

Sets the file to store the experiment setup in (the extensions determines the type).

Parameters:

value - the file

getOutputFile

public PlaceholderFile getOutputFile()

Returns the file to store the experiment in.

Returns:

the file

outputFileTipText

public String outputFileTipText()

Returns the tip text for this property.

Returns:

tip text for this property suitable for displaying in the GUI or for listing the options.

accepts

public Class[] accepts()

Returns the class that the consumer accepts.

Returns:

weka.classifiers.Classifier[].class

setUp

public String setUp()

Initializes the item for flow execution.

Overrides:

setUp in class AbstractActor

Returns:

null if everything is fine, otherwise error message

doExecute

protected String doExecute()

Executes the flow item.

Specified by:

doExecute in class AbstractActor

Returns:

null if everything is fine, otherwise error message