java.lang.Object
- adams.core.logging.LoggingObject
- - adams.core.logging.CustomLoggingLevelObject
  - - adams.core.option.AbstractOptionHandler
    - - adams.opt.optimise.AbstractFitnessFunction
      - adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

All Implemented Interfaces:

Destroyable, GlobalInfoSupporter, LoggingLevelHandler, LoggingSupporter, OptionHandler, SizeOfHandler, FitnessFunction, Serializable

Direct Known Subclasses:

AttributeSelection
```
public abstract class AbstractWEKAFitnessFunction
extends AbstractFitnessFunction
```
Perform attribute selection using WEKA classification.

Author:

dale

See Also:

Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type Class Description

static class AbstractWEKAFitnessFunction.Measure
The measure to use for evaluating.

Field Summary

Fields
Modifier and Type	Field	Description
`protected weka.classifiers.Classifier`	`m_Classifier`	the classifier to use if no serialized model is given.
`protected String`	`m_ClassIndex`	the class index.
`protected int`	`m_CrossValidationSeed`	the cross-validation seed.
`protected PlaceholderFile`	`m_Dataset`	the filename of the data to use for cross-validation.
`protected int`	`m_Folds`	the number of folds for cross-validation.
`protected boolean`	`m_init`	initialised?
`protected weka.core.Instances`	`m_Instances`	the data to use for cross-validation.
`protected AbstractWEKAFitnessFunction.Measure`	`m_Measure`	the measure to use for evaluating the fitness.
`protected PlaceholderDirectory`	`m_OutputDirectory`	the directory to store the generated ARFF files in.

Fields inherited from class adams.core.option.AbstractOptionHandler
m_OptionManager

Fields inherited from class adams.core.logging.LoggingObject
m_Logger, m_LoggingIsEnabled, m_LoggingLevel

Constructor Summary

Constructors
Constructor Description

AbstractWEKAFitnessFunction()

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`String`	`classifierTipText()`	Returns the tip text for this property.
`String`	`classIndexTipText()`	Returns the tip text for this property.
`String`	`crossValidationSeedTipText()`	Returns the tip text for this property.
`String`	`datasetTipText()`	Returns the tip text for this property.
`void`	`defineOptions()`	Adds options to the internal list of options.
`String`	`foldsTipText()`	Returns the tip text for this property.
`weka.classifiers.Classifier`	`getClassifier()`	Returns the currently set classifier.
`String`	`getClassIndex()`	Returns the current class index.
`int`	`getCrossValidationSeed()`	Returns the current seed value for cross-validation.
`PlaceholderFile`	`getDataset()`	Returns the currently set filename of the dataset for cross-validation.
`int`	`getFolds()`	Returns the number of folds to use in cross-validation.
`weka.core.Instances`	`getInstances()`	Returns the currently set dataset for cross-validation.
`AbstractWEKAFitnessFunction.Measure`	`getMeasure()`	Returns the current measure for evaluating the fitness.
`PlaceholderDirectory`	`getOutputDirectory()`	Returns the currently set directory for the generated ARFF files.
`String`	`globalInfo()`	Returns a string describing the object.
`protected void`	`init()`
`String`	`measureTipText()`	Returns the tip text for this property.
`String`	`outputDirectoryTipText()`	Returns the tip text for this property.
`void`	`setClassifier(weka.classifiers.Classifier value)`	Sets the classifier to use (if no serialized model is used).
`void`	`setClassIndex(String value)`	Sets the class index.
`void`	`setCrossValidationSeed(int value)`	Sets the seed value to use for cross-validation.
`void`	`setDataset(PlaceholderFile value)`	Sets the filename of the dataset to use for cross-validation.
`void`	`setFolds(int value)`	Sets the number of folds to use in cross-validation.
`void`	`setInstances(weka.core.Instances value)`	Sets the data to use for cross-validation.
`void`	`setMeasure(AbstractWEKAFitnessFunction.Measure value)`	Sets the measure used for evaluating the fitness.
`void`	`setOutputDirectory(PlaceholderDirectory value)`	Sets the directory for the generated ARFF files.

Methods inherited from class adams.opt.optimise.AbstractFitnessFunction
newBest

Methods inherited from class adams.core.option.AbstractOptionHandler
cleanUpOptions, destroy, finishInit, getDefaultLoggingLevel, getOptionManager, initialize, loggingLevelTipText, newOptionManager, reset, setLoggingLevel, toCommandLine, toString

Methods inherited from class adams.core.logging.LoggingObject
configureLogger, getLogger, getLoggingLevel, initializeLogging, isLoggingEnabled, sizeOf

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

Methods inherited from interface adams.opt.optimise.FitnessFunction
evaluate

Methods inherited from interface adams.core.logging.LoggingLevelHandler
getLoggingLevel

- Field Detail
  - m_Instances
```
protected weka.core.Instances m_Instances
```
    the data to use for cross-validation.
  - m_Dataset
```
protected PlaceholderFile m_Dataset
```
    the filename of the data to use for cross-validation.
  - m_Classifier
```
protected weka.classifiers.Classifier m_Classifier
```
    the classifier to use if no serialized model is given.
  - m_OutputDirectory
```
protected PlaceholderDirectory m_OutputDirectory
```
    the directory to store the generated ARFF files in.
  - m_Folds
```
protected int m_Folds
```
    the number of folds for cross-validation.
  - m_CrossValidationSeed
```
protected int m_CrossValidationSeed
```
    the cross-validation seed.
  - m_ClassIndex
```
protected String m_ClassIndex
```
    the class index.
  - m_Measure
```
protected AbstractWEKAFitnessFunction.Measure m_Measure
```
    the measure to use for evaluating the fitness.
  - m_init
```
protected boolean m_init
```
    initialised?
- Constructor Detail
  - AbstractWEKAFitnessFunction
```
public AbstractWEKAFitnessFunction()
```
- Method Detail
  - defineOptions
```
public void defineOptions()
```
    Adds options to the internal list of options.
    
    Specified by:
    
    defineOptions in interface OptionHandler
    
    Overrides:
    
    defineOptions in class AbstractOptionHandler
  - setFolds
```
public void setFolds(int value)
```
    Sets the number of folds to use in cross-validation.
    
    Parameters:
    
    value - the number of folds
  - getFolds
```
public int getFolds()
```
    Returns the number of folds to use in cross-validation.
    
    Returns:
    
    the number of 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.
  - setCrossValidationSeed
```
public void setCrossValidationSeed(int value)
```
    Sets the seed value to use for cross-validation.
    
    Parameters:
    
    value - the seed to use
  - getCrossValidationSeed
```
public int getCrossValidationSeed()
```
    Returns the current seed value for cross-validation.
    
    Returns:
    
    the seed value
  - crossValidationSeedTipText
```
public String crossValidationSeedTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - setInstances
```
public void setInstances(weka.core.Instances value)
```
    Sets the data to use for cross-validation.
    
    Parameters:
    
    value - the dataset
  - getInstances
```
public weka.core.Instances getInstances()
```
    Returns the currently set dataset for cross-validation.
    
    Returns:
    
    the dataset
  - setDataset
```
public void setDataset(PlaceholderFile value)
```
    Sets the filename of the dataset to use for cross-validation.
    
    Parameters:
    
    value - the filename
  - getDataset
```
public PlaceholderFile getDataset()
```
    Returns the currently set filename of the dataset for cross-validation.
    
    Returns:
    
    the filename
  - datasetTipText
```
public String datasetTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - setClassifier
```
public void setClassifier(weka.classifiers.Classifier value)
```
    Sets the classifier to use (if no serialized model is used).
    
    Parameters:
    
    value - the classifier
  - getClassifier
```
public weka.classifiers.Classifier getClassifier()
```
    Returns the currently set classifier.
    
    Returns:
    
    the classifier
  - classifierTipText
```
public String classifierTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - setOutputDirectory
```
public void setOutputDirectory(PlaceholderDirectory value)
```
    Sets the directory for the generated ARFF files.
    
    Parameters:
    
    value - the directory
  - getOutputDirectory
```
public PlaceholderDirectory getOutputDirectory()
```
    Returns the currently set directory for the generated ARFF files.
    
    Returns:
    
    the directory
  - outputDirectoryTipText
```
public String outputDirectoryTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - setClassIndex
```
public void setClassIndex(String value)
```
    Sets the class index.
    
    Parameters:
    
    value - the class index
  - getClassIndex
```
public String getClassIndex()
```
    Returns the current class index.
    
    Returns:
    
    the class index
  - classIndexTipText
```
public String classIndexTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - setMeasure
```
public void setMeasure(AbstractWEKAFitnessFunction.Measure value)
```
    Sets the measure used for evaluating the fitness.
    
    Parameters:
    
    value - the fitness measure
  - getMeasure
```
public AbstractWEKAFitnessFunction.Measure getMeasure()
```
    Returns the current measure for evaluating the fitness.
    
    Returns:
    
    the measure
  - measureTipText
```
public String measureTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property suitable for displaying in the GUI or for listing the options.
  - globalInfo
```
public String globalInfo()
```
    Description copied from class: AbstractOptionHandler
    
    Returns a string describing the object.
    
    Specified by:
    
    globalInfo in interface GlobalInfoSupporter
    
    Specified by:
    
    globalInfo in class AbstractOptionHandler
    
    Returns:
    
    a description suitable for displaying in the gui
  - init
```
protected void init()
```

Class AbstractWEKAFitnessFunction

Nested Class Summary

Field Summary

Fields inherited from class adams.core.option.AbstractOptionHandler

Fields inherited from class adams.core.logging.LoggingObject

Constructor Summary

Method Summary

Methods inherited from class adams.opt.optimise.AbstractFitnessFunction

Methods inherited from class adams.core.option.AbstractOptionHandler

Methods inherited from class adams.core.logging.LoggingObject

Methods inherited from class java.lang.Object

Methods inherited from interface adams.opt.optimise.FitnessFunction

Methods inherited from interface adams.core.logging.LoggingLevelHandler

Field Detail

m_Instances

m_Dataset

m_Classifier

m_OutputDirectory

m_Folds

m_CrossValidationSeed

m_ClassIndex

m_Measure

m_init

Constructor Detail

AbstractWEKAFitnessFunction

Method Detail

defineOptions

setFolds

getFolds

foldsTipText

setCrossValidationSeed

getCrossValidationSeed

crossValidationSeedTipText

setInstances

getInstances

setDataset

getDataset

datasetTipText

setClassifier

getClassifier

classifierTipText

setOutputDirectory

getOutputDirectory

outputDirectoryTipText

setClassIndex

getClassIndex

classIndexTipText

setMeasure

getMeasure

measureTipText

globalInfo

init