Class MultiLabelRandomAMRules
- java.lang.Object
-
- moa.AbstractMOAObject
-
- moa.options.AbstractOptionHandler
-
- moa.classifiers.AbstractClassifier
-
- moa.classifiers.AbstractMultiLabelLearner
-
- moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- All Implemented Interfaces:
Configurable
,Serializable
,CapabilitiesHandler
,Classifier
,MultiLabelLearner
,MultiTargetRegressor
,AWTRenderable
,Learner<Example<Instance>>
,MOAObject
,OptionHandler
- Direct Known Subclasses:
RandomAMRules
public class MultiLabelRandomAMRules extends AbstractMultiLabelLearner implements MultiTargetRegressor
- See Also:
- Serialized Form
-
-
Field Summary
Fields Modifier and Type Field Description ClassOption
baseLearnerOption
protected AMRulesMultiLabelLearner[]
ensemble
IntOption
ensembleSizeOption
protected MultiLabelErrorMeasurer[]
errorMeasurer
ClassOption
errorMeasurerOption
protected FeatureRanking
featureRanking
ClassOption
featureRankingOption
protected boolean
isRegression
FloatOption
numAttributesPercentageOption
IntOption
randomSeedOption
FlagOption
useBaggingOption
IntOption
VerbosityOption
ClassOption
votingFunctionOption
MultiChoiceOption
votingTypeOption
-
Fields inherited from class moa.classifiers.AbstractClassifier
classifierRandom, modelContext, randomSeed, trainingWeightSeenByModel
-
Fields inherited from class moa.options.AbstractOptionHandler
config
-
-
Constructor Summary
Constructors Constructor Description MultiLabelRandomAMRules()
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description void
getModelDescription(StringBuilder out, int indent)
Returns a string representation of the model.protected Measurement[]
getModelMeasurementsImpl()
Gets the current measurements of this classifier.
The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods.Prediction
getPredictionForInstance(MultiLabelInstance inst)
boolean
isRandomizable()
Gets whether this learner needs a random seed.void
resetLearningImpl()
Resets this classifier.void
trainOnInstanceImpl(MultiLabelInstance instance)
-
Methods inherited from class moa.classifiers.AbstractMultiLabelLearner
getPredictionForInstance, getPredictionForInstance, getVotesForInstance, trainOnInstanceImpl
-
Methods inherited from class moa.classifiers.AbstractClassifier
contextIsCompatible, copy, correctlyClassifies, defineImmutableCapabilities, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getModel, getModelContext, getModelMeasurements, getNominalValueString, getPurposeString, getSubClassifiers, getSublearners, getVotesForInstance, modelAttIndexToInstanceAttIndex, modelAttIndexToInstanceAttIndex, prepareForUseImpl, resetLearning, setModelContext, setRandomSeed, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance, trainOnInstance
-
Methods inherited from class moa.options.AbstractOptionHandler
getCLICreationString, getOptions, getPreparedClassOption, prepareClassOptions, prepareForUse, prepareForUse
-
Methods inherited from class moa.AbstractMOAObject
copy, measureByteSize, measureByteSize, toString
-
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
-
Methods inherited from interface moa.gui.AWTRenderable
getAWTRenderer
-
Methods inherited from interface moa.capabilities.CapabilitiesHandler
getCapabilities
-
Methods inherited from interface moa.classifiers.Classifier
copy, correctlyClassifies, getPredictionForInstance, getSubClassifiers, getVotesForInstance, trainOnInstance
-
Methods inherited from interface moa.learners.Learner
getModel, getModelContext, getModelMeasurements, getPredictionForInstance, getSublearners, getVotesForInstance, resetLearning, setModelContext, setRandomSeed, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance
-
Methods inherited from interface moa.MOAObject
getDescription, measureByteSize
-
Methods inherited from interface moa.options.OptionHandler
getCLICreationString, getOptions, getPurposeString, prepareForUse, prepareForUse
-
-
-
-
Field Detail
-
VerbosityOption
public IntOption VerbosityOption
-
baseLearnerOption
public ClassOption baseLearnerOption
-
ensembleSizeOption
public IntOption ensembleSizeOption
-
numAttributesPercentageOption
public FloatOption numAttributesPercentageOption
-
useBaggingOption
public FlagOption useBaggingOption
-
votingFunctionOption
public ClassOption votingFunctionOption
-
votingTypeOption
public MultiChoiceOption votingTypeOption
-
randomSeedOption
public IntOption randomSeedOption
-
ensemble
protected AMRulesMultiLabelLearner[] ensemble
-
errorMeasurer
protected MultiLabelErrorMeasurer[] errorMeasurer
-
errorMeasurerOption
public ClassOption errorMeasurerOption
-
featureRankingOption
public ClassOption featureRankingOption
-
isRegression
protected boolean isRegression
-
featureRanking
protected FeatureRanking featureRanking
-
-
Method Detail
-
resetLearningImpl
public void resetLearningImpl()
Description copied from class:AbstractClassifier
Resets this classifier. It must be similar to starting a new classifier from scratch.
The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods. Note that this will produce compiler errors if not overridden.- Specified by:
resetLearningImpl
in classAbstractClassifier
-
trainOnInstanceImpl
public void trainOnInstanceImpl(MultiLabelInstance instance)
- Specified by:
trainOnInstanceImpl
in interfaceMultiLabelLearner
- Specified by:
trainOnInstanceImpl
in classAbstractMultiLabelLearner
-
getPredictionForInstance
public Prediction getPredictionForInstance(MultiLabelInstance inst)
- Specified by:
getPredictionForInstance
in interfaceMultiLabelLearner
- Specified by:
getPredictionForInstance
in classAbstractMultiLabelLearner
-
getModelMeasurementsImpl
protected Measurement[] getModelMeasurementsImpl()
Description copied from class:AbstractClassifier
Gets the current measurements of this classifier.
The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods. Note that this will produce compiler errors if not overridden.- Specified by:
getModelMeasurementsImpl
in classAbstractClassifier
- Returns:
- an array of measurements to be used in evaluation tasks
-
getModelDescription
public void getModelDescription(StringBuilder out, int indent)
Description copied from class:AbstractClassifier
Returns a string representation of the model.- Specified by:
getModelDescription
in classAbstractClassifier
- Parameters:
out
- the stringbuilder to add the descriptionindent
- the number of characters to indent
-
isRandomizable
public boolean isRandomizable()
Description copied from interface:Learner
Gets whether this learner needs a random seed. Examples of methods that needs a random seed are bagging and boosting.- Specified by:
isRandomizable
in interfaceLearner<Example<Instance>>
- Returns:
- true if the learner needs a random seed.
-
-