public abstract class AMRulesMultiLabelLearner extends AbstractMultiLabelLearner implements MultiLabelLearner
Modifier and Type | Field and Description |
---|---|
ClassOption |
anomalyDetector |
protected double |
attributesPercentage |
ClassOption |
changeDetector |
protected MultiLabelRule |
defaultRule |
FlagOption |
dropOldRuleAfterExpansionOption |
ClassOption |
errorMeasurerOption |
ClassOption |
featureRankingOption |
IntOption |
gracePeriodOption |
ClassOption |
inputSelectorOption |
ClassOption |
learnerOption |
ClassOption |
nominalObserverOption |
ClassOption |
numericObserverOption |
protected ObserverMOAObject |
observer |
ClassOption |
outputSelectorOption |
IntOption |
randomSeedOption |
protected int |
ruleNumberID |
protected MultiLabelRuleSet |
ruleSet |
FloatOption |
splitConfidenceOption |
ClassOption |
splitCriterionOption |
protected double[] |
statistics |
FloatOption |
tieThresholdOption |
FlagOption |
unorderedRulesOption |
IntOption |
VerbosityOption |
ClassOption |
weightedVoteOption |
classifierRandom, downSampleRatio, modelContext, randomSeed, trainingWeightSeenByModel
config
Constructor and Description |
---|
AMRulesMultiLabelLearner() |
AMRulesMultiLabelLearner(double attributesPercentage) |
Modifier and Type | Method and Description |
---|---|
protected void |
debug(String string,
int level)
Print to console
|
protected double[] |
defaultRuleErrors(Prediction vote) |
double |
getAttributesPercentage() |
protected double |
getAverageInputs() |
protected double |
getAverageOutputs() |
void |
getModelDescription(StringBuilder out,
int indent)
print GUI learn model
|
protected Measurement[] |
getModelMeasurementsImpl()
print GUI evaluate model
|
Prediction |
getPredictionForInstance(MultiLabelInstance inst) |
ErrorWeightedVoteMultiLabel |
getVotes(MultiLabelInstance instance)
getVotes extension of the instance method getVotesForInstance
in moa.classifier.java
returns the prediction of the instance.
|
boolean |
isRandomizable()
Gets whether this learner needs a random seed.
|
protected abstract MultiLabelRule |
newDefaultRule() |
ErrorWeightedVoteMultiLabel |
newErrorWeightedVote() |
void |
PrintRuleSet() |
void |
resetLearningImpl()
Resets this classifier.
|
void |
setAttributesPercentage(double attributesPercentage) |
void |
setObserver(ObserverMOAObject observer) |
void |
setRandomSeed(int randomSeed)
Sets the seed for random number generation.
|
protected void |
setRuleOptions(MultiLabelRule rule) |
void |
trainOnInstanceImpl(MultiLabelInstance instance) |
protected void |
VerboseToConsole(MultiLabelInstance inst) |
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, 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, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance
getCLICreationString, getOptions, getPurposeString, prepareForUse, prepareForUse
getDescription, measureByteSize
getAWTRenderer
protected MultiLabelRuleSet ruleSet
protected MultiLabelRule defaultRule
protected int ruleNumberID
protected double[] statistics
protected ObserverMOAObject observer
public FloatOption splitConfidenceOption
public FloatOption tieThresholdOption
public IntOption gracePeriodOption
public ClassOption learnerOption
public FlagOption unorderedRulesOption
public FlagOption dropOldRuleAfterExpansionOption
public ClassOption changeDetector
public ClassOption anomalyDetector
public ClassOption splitCriterionOption
public ClassOption errorMeasurerOption
public ClassOption weightedVoteOption
public ClassOption numericObserverOption
public ClassOption nominalObserverOption
public IntOption VerbosityOption
public ClassOption outputSelectorOption
public ClassOption inputSelectorOption
public IntOption randomSeedOption
public ClassOption featureRankingOption
protected double attributesPercentage
public AMRulesMultiLabelLearner()
public AMRulesMultiLabelLearner(double attributesPercentage)
public double getAttributesPercentage()
public void setAttributesPercentage(double attributesPercentage)
public Prediction getPredictionForInstance(MultiLabelInstance inst)
getPredictionForInstance
in interface MultiLabelLearner
getPredictionForInstance
in class AbstractMultiLabelLearner
public ErrorWeightedVoteMultiLabel getVotes(MultiLabelInstance instance)
protected double[] defaultRuleErrors(Prediction vote)
public boolean isRandomizable()
Learner
isRandomizable
in interface Learner<Example<Instance>>
public void trainOnInstanceImpl(MultiLabelInstance instance)
trainOnInstanceImpl
in interface MultiLabelLearner
trainOnInstanceImpl
in class AbstractMultiLabelLearner
protected Measurement[] getModelMeasurementsImpl()
getModelMeasurementsImpl
in class AbstractClassifier
protected double getAverageInputs()
protected double getAverageOutputs()
public void getModelDescription(StringBuilder out, int indent)
getModelDescription
in class AbstractClassifier
out
- the stringbuilder to add the descriptionindent
- the number of characters to indentprotected void debug(String string, int level)
string
- protected void VerboseToConsole(MultiLabelInstance inst)
public void PrintRuleSet()
public void resetLearningImpl()
AbstractClassifier
resetLearningImpl
in class AbstractClassifier
protected void setRuleOptions(MultiLabelRule rule)
protected abstract MultiLabelRule newDefaultRule()
public ErrorWeightedVoteMultiLabel newErrorWeightedVote()
public void setRandomSeed(int randomSeed)
Learner
setRandomSeed
in interface Learner<Example<Instance>>
setRandomSeed
in class AbstractClassifier
randomSeed
- the seedpublic void setObserver(ObserverMOAObject observer)
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