Class AbstractWEKAFitnessFunction
- java.lang.Object
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- adams.core.logging.LoggingObject
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- adams.core.logging.CustomLoggingLevelObject
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- adams.core.option.AbstractOptionHandler
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- adams.opt.optimise.AbstractFitnessFunction
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- adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction
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- All Implemented Interfaces:
adams.core.Destroyable
,adams.core.GlobalInfoSupporter
,adams.core.logging.LoggingLevelHandler
,adams.core.logging.LoggingSupporter
,adams.core.option.OptionHandler
,adams.core.SizeOfHandler
,adams.opt.optimise.FitnessFunction
,Serializable
- Direct Known Subclasses:
AttributeSelection
public abstract class AbstractWEKAFitnessFunction extends adams.opt.optimise.AbstractFitnessFunction
Perform attribute selection using WEKA classification.- Author:
- dale
- See Also:
- Serialized Form
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Nested Class Summary
Nested Classes Modifier and Type Class Description static class
AbstractWEKAFitnessFunction.Measure
The measure to use for evaluating.
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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 adams.core.io.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 adams.core.io.PlaceholderDirectory
m_OutputDirectory
the directory to store the generated ARFF files in.
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Constructor Summary
Constructors Constructor Description AbstractWEKAFitnessFunction()
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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.adams.core.io.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.adams.core.io.PlaceholderDirectory
getOutputDirectory()
Returns the currently set directory for the generated ARFF files.String
globalInfo()
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(adams.core.io.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(adams.core.io.PlaceholderDirectory value)
Sets the directory for the generated ARFF files.-
Methods inherited from class adams.core.option.AbstractOptionHandler
cleanUpOptions, destroy, finishInit, getDefaultLoggingLevel, getOptionManager, initialize, loggingLevelTipText, newOptionManager, reset, setLoggingLevel, toCommandLine, toString
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Methods inherited from class adams.core.logging.LoggingObject
configureLogger, getLogger, getLoggingLevel, initializeLogging, isLoggingEnabled, sizeOf
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Field Detail
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m_Instances
protected weka.core.Instances m_Instances
the data to use for cross-validation.
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m_Dataset
protected adams.core.io.PlaceholderFile m_Dataset
the filename of the data to use for cross-validation.
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m_Classifier
protected weka.classifiers.Classifier m_Classifier
the classifier to use if no serialized model is given.
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m_OutputDirectory
protected adams.core.io.PlaceholderDirectory m_OutputDirectory
the directory to store the generated ARFF files in.
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m_Folds
protected int m_Folds
the number of folds for cross-validation.
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m_CrossValidationSeed
protected int m_CrossValidationSeed
the cross-validation seed.
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m_ClassIndex
protected String m_ClassIndex
the class index.
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m_Measure
protected AbstractWEKAFitnessFunction.Measure m_Measure
the measure to use for evaluating the fitness.
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m_init
protected boolean m_init
initialised?
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Method Detail
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defineOptions
public void defineOptions()
Adds options to the internal list of options.- Specified by:
defineOptions
in interfaceadams.core.option.OptionHandler
- Overrides:
defineOptions
in classadams.core.option.AbstractOptionHandler
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setFolds
public void setFolds(int value)
Sets the number of folds to use in cross-validation.- Parameters:
value
- the number of folds
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getFolds
public int getFolds()
Returns the number of folds to use in cross-validation.- Returns:
- the number of folds
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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.
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setCrossValidationSeed
public void setCrossValidationSeed(int value)
Sets the seed value to use for cross-validation.- Parameters:
value
- the seed to use
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getCrossValidationSeed
public int getCrossValidationSeed()
Returns the current seed value for cross-validation.- Returns:
- the seed value
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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.
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setInstances
public void setInstances(weka.core.Instances value)
Sets the data to use for cross-validation.- Parameters:
value
- the dataset
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getInstances
public weka.core.Instances getInstances()
Returns the currently set dataset for cross-validation.- Returns:
- the dataset
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setDataset
public void setDataset(adams.core.io.PlaceholderFile value)
Sets the filename of the dataset to use for cross-validation.- Parameters:
value
- the filename
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getDataset
public adams.core.io.PlaceholderFile getDataset()
Returns the currently set filename of the dataset for cross-validation.- Returns:
- the filename
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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.
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setClassifier
public void setClassifier(weka.classifiers.Classifier value)
Sets the classifier to use (if no serialized model is used).- Parameters:
value
- the classifier
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getClassifier
public weka.classifiers.Classifier getClassifier()
Returns the currently set classifier.- Returns:
- the classifier
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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.
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setOutputDirectory
public void setOutputDirectory(adams.core.io.PlaceholderDirectory value)
Sets the directory for the generated ARFF files.- Parameters:
value
- the directory
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getOutputDirectory
public adams.core.io.PlaceholderDirectory getOutputDirectory()
Returns the currently set directory for the generated ARFF files.- Returns:
- the directory
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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.
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setClassIndex
public void setClassIndex(String value)
Sets the class index.- Parameters:
value
- the class index
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getClassIndex
public String getClassIndex()
Returns the current class index.- Returns:
- the class index
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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.
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setMeasure
public void setMeasure(AbstractWEKAFitnessFunction.Measure value)
Sets the measure used for evaluating the fitness.- Parameters:
value
- the fitness measure
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getMeasure
public AbstractWEKAFitnessFunction.Measure getMeasure()
Returns the current measure for evaluating the fitness.- Returns:
- the measure
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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.
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globalInfo
public String globalInfo()
- Specified by:
globalInfo
in interfaceadams.core.GlobalInfoSupporter
- Specified by:
globalInfo
in classadams.core.option.AbstractOptionHandler
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init
protected void init()
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