ClassificationStatisticsPresenter
, weka.core.AdditionalMeasureProducer
, weka.core.TechnicalInformationHandler
, weka.core.WeightedInstancesHandler
public class IIVotes extends weka.classifiers.RandomizableSingleClassifierEnhancer implements weka.core.WeightedInstancesHandler, weka.core.AdditionalMeasureProducer, weka.core.TechnicalInformationHandler, ClassificationStatisticsPresenter
Modifier and Type | Field | Description |
---|---|---|
static weka.core.Tag[] |
TAGS_AGGREGATION_METHOD |
The aggregation method modes
|
static weka.core.Tag[] |
TAGS_ESTIMATION_CRITERIA |
The estimation criteria modes.
|
Constructor | Description |
---|---|
IIVotes() |
Constructor.
|
Modifier and Type | Method | Description |
---|---|---|
java.lang.String |
aggregationMethodTipText() |
|
void |
buildClassifier(weka.core.Instances data) |
Method building ensemble of classifiers using importance voting.
|
java.lang.String |
classificationStatisticsToString() |
|
double |
classifyInstance(weka.core.Instance instance) |
Classifies a given instance.
|
double[] |
distributionForInstance(weka.core.Instance instance) |
Calculates the class membership probabilities for the given test
instance.
|
java.util.Enumeration<java.lang.String> |
enumerateMeasures() |
Returns an enumeration of the additional measure names.
|
java.lang.String |
estimationCriteriaTipText() |
|
weka.core.SelectedTag |
getAggregationMethod() |
Gets the method used.
|
ClassificationStatisticsCollector |
getClassificationStatisticsCollector() |
|
weka.core.SelectedTag |
getEstimationCriteria() |
Gets the criteria used.
|
double |
getMeasure(java.lang.String additionalMeasureName) |
Returns the value of the named measure.
|
java.lang.String[] |
getOptions() |
Gets the current settings of the classifier.
|
java.lang.String |
getRevision() |
Gets the revision.
|
static double |
getSmoothFactor() |
Gets the smooth factor.
|
weka.core.TechnicalInformation |
getTechnicalInformation() |
Returns an instance of a TechnicalInformation object, containing detailed
information about the technical background of this class, e.g., paper
reference or book this class is based on.
|
int |
getTrainingSetSize() |
Gets the size of each training set, as a percentage of the whole training
set size.
|
java.lang.String |
globalInfo() |
Returns a string describing classifier.
|
java.util.Enumeration |
listOptions() |
Returns an enumeration describing the available options.
|
static void |
main(java.lang.String[] args) |
Main method for testing this class.
|
void |
setAggregationMethod(weka.core.SelectedTag newAggregationMethod) |
Sets the method used.
|
void |
setEstimationCriteria(weka.core.SelectedTag newEstimationCriteria) |
Sets the method used.
|
void |
setOptions(java.lang.String[] options) |
Parses a given list of options.
|
static void |
setSmoothFactor(double newSmoothFactor) |
Sets the smooth factor.
|
void |
setTrainingSetSize(int newTrainingSetSize) |
Sets the size of each training set, as a percentage of the whole training
set size.
|
java.lang.String |
smoothFactorTipText() |
Returns the tip text for this property
|
java.lang.String |
trainingSetSizeTipText() |
Returns the tip text for this property
|
debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
public static final weka.core.Tag[] TAGS_ESTIMATION_CRITERIA
public static final weka.core.Tag[] TAGS_AGGREGATION_METHOD
public java.lang.String estimationCriteriaTipText()
public weka.core.SelectedTag getEstimationCriteria()
public void setEstimationCriteria(weka.core.SelectedTag newEstimationCriteria)
newEstimationCriteria
- the new estimation criteria.public int getTrainingSetSize()
public void setTrainingSetSize(int newTrainingSetSize)
newTrainingSetSize
- the training set size, as a percentage.public java.lang.String trainingSetSizeTipText()
public static double getSmoothFactor()
public static void setSmoothFactor(double newSmoothFactor)
newSmoothFactor
- the new smooth factor.public java.lang.String smoothFactorTipText()
public java.lang.String aggregationMethodTipText()
public weka.core.SelectedTag getAggregationMethod()
public void setAggregationMethod(weka.core.SelectedTag newAggregationMethod)
newAggregationMethod
- the new aggregation method.public void buildClassifier(weka.core.Instances data) throws java.lang.Exception
buildClassifier
in class weka.classifiers.Classifier
data
- the training data to be used for generating the IVotes
classifier.java.lang.Exception
- if the classifier could not be built successfullypublic double classifyInstance(weka.core.Instance instance)
classifyInstance
in class weka.classifiers.Classifier
instance
- the instance to be classifiedpublic double[] distributionForInstance(weka.core.Instance instance) throws java.lang.Exception
distributionForInstance
in class weka.classifiers.Classifier
instance
- the instance to be classifiedjava.lang.Exception
- if distribution can't be computed successfullypublic java.util.Enumeration<java.lang.String> enumerateMeasures()
enumerateMeasures
in interface weka.core.AdditionalMeasureProducer
public double getMeasure(java.lang.String additionalMeasureName)
getMeasure
in interface weka.core.AdditionalMeasureProducer
additionalMeasureName
- the name of the measure to query for its valuejava.lang.IllegalArgumentException
- if the named measure is not supportedpublic java.util.Enumeration listOptions()
listOptions
in class weka.classifiers.RandomizableSingleClassifierEnhancer
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-W classname
Specify the full class name of the base learner.
-N num
Sets the size of each training set, as a percentage of the whole training
set size.
-F num
Sets the smooth factor as value in [0;1].
-S <num>
Random number seed. (default 1)
-D
If set, classifier is run in debug mode and may output additional info to
the console
Options after -- are passed to the designated classifier.
setOptions
in class weka.classifiers.RandomizableSingleClassifierEnhancer
options
- the list of options as an array of stringsjava.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in class weka.classifiers.RandomizableSingleClassifierEnhancer
public java.lang.String globalInfo()
public weka.core.TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface weka.core.TechnicalInformationHandler
public java.lang.String getRevision()
public static void main(java.lang.String[] args)
args
- the optionspublic java.lang.String classificationStatisticsToString()
classificationStatisticsToString
in interface ClassificationStatisticsPresenter
public ClassificationStatisticsCollector getClassificationStatisticsCollector()
getClassificationStatisticsCollector
in interface ClassificationStatisticsPresenter