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java.lang.Objectweka.experiment.SemiSupClustererSplitEvaluator
A SplitEvaluator that produces results for a semi-supervised clustering scheme
on a nominal class attribute.
-W clustername
Specify the full class name of the clusterer to evaluate.
-C class index
The index of the class for which statistics are to
be output. (default 1)
Field Summary | |
protected Clusterer |
m_Clusterer
The semi-supervised clusterer used for evaluation |
protected java.lang.String |
m_ClustererOptions
The clusterer options (if any) |
protected java.lang.String |
m_ClustererVersion
The clusterer version |
protected java.lang.String |
m_result
Holds the statistics for the most recent application of the clusterer |
Constructor Summary | |
SemiSupClustererSplitEvaluator()
No args constructor. |
Method Summary | |
java.lang.String |
clustererTipText()
Returns the tip text for this property |
int |
getClassForIRStatistics()
Get the value of ClassForIRStatistics. |
Clusterer |
getClusterer()
Get the value of Clusterer. |
java.lang.Object[] |
getKey()
Gets the key describing the current SplitEvaluator. |
java.lang.String[] |
getKeyNames()
Gets the names of each of the key columns produced for a single run. |
java.lang.Object[] |
getKeyTypes()
Gets the data types of each of the key columns produced for a single run. |
java.lang.String[] |
getOptions()
Gets the current settings of the Clusterer. |
java.lang.String |
getRawResultOutput()
Gets the raw output from the clusterer |
java.lang.Object[] |
getResult(java.util.ArrayList labeledTrainPairs,
Instances labeledTrain,
Instances unlabeledData,
Instances test,
Instances unlabeledTest)
Gets the results for the supplied train and test datasets. |
java.lang.Object[] |
getResult(Instances unlabeledTrain,
Instances test)
Dummy function, exists just for compatibility with SplitEvaluator interface |
java.lang.Object[] |
getResult(Instances labeledTrain,
Instances unlabeledData,
Instances totalTrainWithLabels,
Instances test,
int startingIndexOfTest)
Gets the results for the supplied train and test datasets. |
java.lang.Object[] |
getResult(Instances labeledTrain,
Instances unlabeledTrain,
Instances test,
int numClasses)
Gets the results for the supplied train and test datasets. |
java.lang.Object[] |
getResult(Instances labeledTrain,
Instances unlabeledTrain,
Instances test,
int numClasses,
int startingIndexOfTest)
Gets the results for the supplied train and test datasets. |
java.lang.String[] |
getResultNames()
Gets the names of each of the result columns produced for a single run. |
java.lang.Object[] |
getResultTypes()
Gets the data types of each of the result columns produced for a single run. |
java.lang.String |
globalInfo()
Returns a string describing this split evaluator |
java.util.Enumeration |
listOptions()
Returns an enumeration describing the available options.. |
void |
setAdditionalMeasures(java.lang.String[] additionalMeasures)
Does nothing, since cluster evaluation does not allow additional measures |
void |
setClassForIRStatistics(int v)
Set the value of ClassForIRStatistics. |
void |
setClusterer(Clusterer newClusterer)
Sets the clusterer. |
void |
setClustererName(java.lang.String newClustererName)
Set the Clusterer to use, given it's class name. |
void |
setOptions(java.lang.String[] options)
Parses a given list of options. |
java.lang.String |
toString()
Returns a text description of the split evaluator. |
protected void |
updateOptions()
Updates the options that the current clusterer is using. |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Field Detail |
protected Clusterer m_Clusterer
protected java.lang.String m_result
protected java.lang.String m_ClustererOptions
protected java.lang.String m_ClustererVersion
Constructor Detail |
public SemiSupClustererSplitEvaluator()
Method Detail |
public void setAdditionalMeasures(java.lang.String[] additionalMeasures)
setAdditionalMeasures
in interface SplitEvaluator
additionalMeasures
- a list of method namespublic java.lang.String globalInfo()
public java.util.Enumeration listOptions()
listOptions
in interface OptionHandler
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-W classname
Specify the full class name of the clusterer to evaluate.
-C class index
The index of the class for which IR statistics are to
be output. (default 1)
All option after -- will be passed to the clusterer.
setOptions
in interface OptionHandler
options
- the list of options as an array of strings
java.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface OptionHandler
public java.lang.Object[] getKeyTypes()
getKeyTypes
in interface SplitEvaluator
public java.lang.String[] getKeyNames()
getKeyNames
in interface SplitEvaluator
public java.lang.Object[] getKey()
getKey
in interface SplitEvaluator
public java.lang.Object[] getResultTypes()
getResultTypes
in interface SplitEvaluator
public java.lang.String[] getResultNames()
getResultNames
in interface SplitEvaluator
public java.lang.Object[] getResult(Instances unlabeledTrain, Instances test)
getResult
in interface SplitEvaluator
unlabeledTrain
- the training Instances.test
- the testing Instances.
public java.lang.Object[] getResult(java.util.ArrayList labeledTrainPairs, Instances labeledTrain, Instances unlabeledData, Instances test, Instances unlabeledTest) throws java.lang.Exception
labeledTrainPairs
- the constraint pairs having labels on themlabeledTrain
- the labeled training Instances.unlabeledData
- the unlabeled training (+ test for transductive) Instances.test
- the testing Instances.
java.lang.Exception
- if a problem occurs while getting the resultspublic java.lang.Object[] getResult(Instances labeledTrain, Instances unlabeledTrain, Instances test, int numClasses) throws java.lang.Exception
labeledTrain
- the labeled training Instances.unlabeledTrain
- the unlabeled training Instances.test
- the testing Instances.
java.lang.Exception
- if a problem occurs while getting the resultspublic java.lang.Object[] getResult(Instances labeledTrain, Instances unlabeledData, Instances totalTrainWithLabels, Instances test, int startingIndexOfTest) throws java.lang.Exception
labeledTrain
- the labeled training Instances.unlabeledData
- the unlabeled training (+ test for transductive) Instances.test
- the testing Instances.startingIndexOfTest
- from where test data starts in unlabeledData, useful if clustering is transductive
java.lang.Exception
- if a problem occurs while getting the resultspublic java.lang.Object[] getResult(Instances labeledTrain, Instances unlabeledTrain, Instances test, int numClasses, int startingIndexOfTest) throws java.lang.Exception
labeledTrain
- the labeled training Instances.unlabeledTrain
- the unlabeled training Instances.test
- the testing Instances.startingIndexOfTest
- from where test data starts in unlabeledData, useful if clustering is transductive
java.lang.Exception
- if a problem occurs while getting the resultspublic java.lang.String clustererTipText()
public Clusterer getClusterer()
public void setClusterer(Clusterer newClusterer)
newClusterer
- the new clusterer to use.public int getClassForIRStatistics()
public void setClassForIRStatistics(int v)
v
- Value to assign to ClassForIRStatistics.protected void updateOptions()
public void setClustererName(java.lang.String newClustererName) throws java.lang.Exception
java.lang.Exception
- if the class name is invalid.public java.lang.String getRawResultOutput()
getRawResultOutput
in interface SplitEvaluator
public java.lang.String toString()
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