public class MultiLabelRandomAMRules extends AbstractMultiLabelLearner implements MultiTargetRegressor
Modifier and Type | Field and 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 |
classifierRandom, downSampleRatio, modelContext, randomSeed, trainingWeightSeenByModel
config
Constructor and Description |
---|
MultiLabelRandomAMRules() |
Modifier and Type | Method and 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) |
getPredictionForInstance, getPredictionForInstance, getVotesForInstance, trainOnInstanceImpl
contextIsCompatible, copy, correctlyClassifies, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getDownSampleRatio, getModel, getModelContext, getModelMeasurements, getNominalValueString, getPurposeString, getSubClassifiers, getSublearners, getVotesForInstance, modelAttIndexToInstanceAttIndex, modelAttIndexToInstanceAttIndex, prepareForUseImpl, resetLearning, setModelContext, setRandomSeed, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance, trainOnInstance, updateDownSampleRatio
getCLICreationString, getOptions, getPreparedClassOption, prepareClassOptions, prepareForUse, prepareForUse
copy, measureByteSize, measureByteSize, toString
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
copy, correctlyClassifies, getPredictionForInstance, getSubClassifiers, getVotesForInstance, trainOnInstance
getModel, getModelContext, getModelMeasurements, getPredictionForInstance, getSublearners, getVotesForInstance, resetLearning, setModelContext, setRandomSeed, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance
getCLICreationString, getOptions, getPurposeString, prepareForUse, prepareForUse
getDescription, measureByteSize
getAWTRenderer
public IntOption VerbosityOption
public ClassOption baseLearnerOption
public IntOption ensembleSizeOption
public FloatOption numAttributesPercentageOption
public FlagOption useBaggingOption
public ClassOption votingFunctionOption
public MultiChoiceOption votingTypeOption
public IntOption randomSeedOption
protected AMRulesMultiLabelLearner[] ensemble
protected MultiLabelErrorMeasurer[] errorMeasurer
public ClassOption errorMeasurerOption
public ClassOption featureRankingOption
protected boolean isRegression
protected FeatureRanking featureRanking
public void resetLearningImpl()
AbstractClassifier
resetLearningImpl
in class AbstractClassifier
public void trainOnInstanceImpl(MultiLabelInstance instance)
trainOnInstanceImpl
in interface MultiLabelLearner
trainOnInstanceImpl
in class AbstractMultiLabelLearner
public Prediction getPredictionForInstance(MultiLabelInstance inst)
getPredictionForInstance
in interface MultiLabelLearner
getPredictionForInstance
in class AbstractMultiLabelLearner
protected Measurement[] getModelMeasurementsImpl()
AbstractClassifier
getModelMeasurementsImpl
in class AbstractClassifier
public void getModelDescription(StringBuilder out, int indent)
AbstractClassifier
getModelDescription
in class AbstractClassifier
out
- the stringbuilder to add the descriptionindent
- the number of characters to indentpublic boolean isRandomizable()
Learner
isRandomizable
in interface Learner<Example<Instance>>
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