Package weka.classifiers.meta
Class ThresholdedBinaryClassification
- java.lang.Object
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- weka.classifiers.AbstractClassifier
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- weka.classifiers.SingleClassifierEnhancer
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- weka.classifiers.meta.ThresholdedBinaryClassification
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- All Implemented Interfaces:
Serializable
,Cloneable
,weka.classifiers.Classifier
,weka.core.BatchPredictor
,weka.core.CapabilitiesHandler
,weka.core.CapabilitiesIgnorer
,weka.core.CommandlineRunnable
,ModelOutputHandler
,weka.core.OptionHandler
,weka.core.RevisionHandler
public class ThresholdedBinaryClassification extends weka.classifiers.SingleClassifierEnhancer implements ModelOutputHandler
Meta classifier for binary classification problems that allows to specify a minimum probability threshold for one of the labels. If this label achieves at least this probability then this label gets chosen, otherwise the other one. Valid options are:-label <value> The index of the label to check. (default: first)
-min-probability <value> The minimum probability for the label (0-1). (default: 0.5)
-suppress-model-output If enabled, suppresses any large model output.
-W Full name of base classifier. (default: weka.classifiers.rules.ZeroR)
-output-debug-info If set, classifier is run in debug mode and may output additional info to the console
-do-not-check-capabilities If set, classifier capabilities are not checked before classifier is built (use with caution).
Options specific to classifier weka.classifiers.rules.ZeroR:
-output-debug-info If set, classifier is run in debug mode and may output additional info to the console
-do-not-check-capabilities If set, classifier capabilities are not checked before classifier is built (use with caution).
- Version:
- $Revision$
- Author:
- FracPete (fracpete at waikato dot ac dot nz)
- See Also:
- Serialized Form
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Field Summary
Fields Modifier and Type Field Description static String
LABEL
protected int
m_ActualLabel
the index of the label to check.protected WekaLabelIndex
m_Label
the label to check.protected double
m_MinProbability
the minimum probability for the label.protected int
m_OtherLabel
the index of the other label.protected boolean
m_SuppressModelOutput
whether to suppress the model output.static String
MIN_PROBABILITY
static String
SUPPRESS_MODEL_OUTPUT
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Constructor Summary
Constructors Constructor Description ThresholdedBinaryClassification()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description void
buildClassifier(weka.core.Instances data)
Builds the classifier with the training data.double[]
distributionForInstance(weka.core.Instance instance)
Returns the class distribution for the instance.weka.core.Capabilities
getCapabilities()
Returns the ensemble's capabilities.protected WekaLabelIndex
getDefaultLabel()
Returns the default label index.protected double
getDefaultMinProbability()
Returns the default minimum probability.WekaLabelIndex
getLabel()
Returns the label index.double
getMinProbability()
Returns the minimum probability for the selected label.String[]
getOptions()
Gets the current option settings for the OptionHandler.boolean
getSuppressModelOutput()
Returns whether to output the model with the toString() method or not.String
globalInfo()
Returns a string describing classifier.String
labelTipText()
Returns the tip text for this property.Enumeration
listOptions()
Returns an enumeration describing the available options.String
minProbabilityTipText()
Returns the tip text for this property.void
setLabel(WekaLabelIndex value)
Sets the label index to use.void
setMinProbability(double value)
Sets the minimum probability for the selected label.void
setOptions(String[] options)
Sets the OptionHandler's options using the given list.void
setSuppressModelOutput(boolean value)
Sets whether to output the model with the toString() method or not.String
suppressModelOutputTipText()
Returns the tip text for this property.String
toString()
Returns the classifier's model.-
Methods inherited from class weka.classifiers.SingleClassifierEnhancer
classifierTipText, defaultClassifierOptions, defaultClassifierString, getClassifier, getClassifierSpec, postExecution, preExecution, setClassifier
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Methods inherited from class weka.classifiers.AbstractClassifier
batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, getRevision, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces
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Field Detail
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LABEL
public static final String LABEL
- See Also:
- Constant Field Values
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MIN_PROBABILITY
public static final String MIN_PROBABILITY
- See Also:
- Constant Field Values
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SUPPRESS_MODEL_OUTPUT
public static final String SUPPRESS_MODEL_OUTPUT
- See Also:
- Constant Field Values
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m_Label
protected WekaLabelIndex m_Label
the label to check.
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m_ActualLabel
protected int m_ActualLabel
the index of the label to check.
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m_OtherLabel
protected int m_OtherLabel
the index of the other label.
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m_MinProbability
protected double m_MinProbability
the minimum probability for the label.
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m_SuppressModelOutput
protected boolean m_SuppressModelOutput
whether to suppress the model output.
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Method Detail
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globalInfo
public String globalInfo()
Returns a string describing classifier.- Returns:
- a description suitable for displaying in the explorer/experimenter gui
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getDefaultLabel
protected WekaLabelIndex getDefaultLabel()
Returns the default label index.- Returns:
- the default
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setLabel
public void setLabel(WekaLabelIndex value)
Sets the label index to use.- Parameters:
value
- the label index
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getLabel
public WekaLabelIndex getLabel()
Returns the label index.- Returns:
- the label index
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labelTipText
public String labelTipText()
Returns the tip text for this property.- Returns:
- tip text for this property suitable for displaying in the gui
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getDefaultMinProbability
protected double getDefaultMinProbability()
Returns the default minimum probability.- Returns:
- the default
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setMinProbability
public void setMinProbability(double value)
Sets the minimum probability for the selected label.- Parameters:
value
- the probability
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getMinProbability
public double getMinProbability()
Returns the minimum probability for the selected label.- Returns:
- the probability
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minProbabilityTipText
public String minProbabilityTipText()
Returns the tip text for this property.- Returns:
- tip text for this property suitable for displaying in the gui
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setSuppressModelOutput
public void setSuppressModelOutput(boolean value)
Sets whether to output the model with the toString() method or not.- Specified by:
setSuppressModelOutput
in interfaceModelOutputHandler
- Parameters:
value
- true if to suppress model output
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getSuppressModelOutput
public boolean getSuppressModelOutput()
Returns whether to output the model with the toString() method or not.- Specified by:
getSuppressModelOutput
in interfaceModelOutputHandler
- Returns:
- the label index
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suppressModelOutputTipText
public String suppressModelOutputTipText()
Returns the tip text for this property.- Specified by:
suppressModelOutputTipText
in interfaceModelOutputHandler
- Returns:
- tip text for this property suitable for displaying in the gui
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listOptions
public Enumeration listOptions()
Returns an enumeration describing the available options.- Specified by:
listOptions
in interfaceweka.core.OptionHandler
- Overrides:
listOptions
in classweka.classifiers.SingleClassifierEnhancer
- Returns:
- an enumeration of all the available options.
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setOptions
public void setOptions(String[] options) throws Exception
Sets the OptionHandler's options using the given list. All options will be set (or reset) during this call (i.e. incremental setting of options is not possible).- Specified by:
setOptions
in interfaceweka.core.OptionHandler
- Overrides:
setOptions
in classweka.classifiers.SingleClassifierEnhancer
- Parameters:
options
- the list of options as an array of strings- Throws:
Exception
- if an option is not supported
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getOptions
public String[] getOptions()
Gets the current option settings for the OptionHandler.- Specified by:
getOptions
in interfaceweka.core.OptionHandler
- Overrides:
getOptions
in classweka.classifiers.SingleClassifierEnhancer
- Returns:
- the list of current option settings as an array of strings
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getCapabilities
public weka.core.Capabilities getCapabilities()
Returns the ensemble's capabilities.- Specified by:
getCapabilities
in interfaceweka.core.CapabilitiesHandler
- Specified by:
getCapabilities
in interfaceweka.classifiers.Classifier
- Overrides:
getCapabilities
in classweka.classifiers.SingleClassifierEnhancer
- Returns:
- the capabilities
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buildClassifier
public void buildClassifier(weka.core.Instances data) throws Exception
Builds the classifier with the training data.- Specified by:
buildClassifier
in interfaceweka.classifiers.Classifier
- Parameters:
data
- the training data- Throws:
Exception
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distributionForInstance
public double[] distributionForInstance(weka.core.Instance instance) throws Exception
Returns the class distribution for the instance.- Specified by:
distributionForInstance
in interfaceweka.classifiers.Classifier
- Overrides:
distributionForInstance
in classweka.classifiers.AbstractClassifier
- Parameters:
instance
- the instance to make the prediction for- Returns:
- the class distribution
- Throws:
Exception
- if classification fails
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