public class MajorityLabelset extends AbstractMultiLabelLearner implements MultiTargetRegressor
classifierRandom, downSampleRatio, modelContext, randomSeed, randomSeedOption, trainingWeightSeenByModel
config
Constructor and Description |
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MajorityLabelset() |
Modifier and Type | Method and Description |
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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 x) |
String |
getPurposeString()
Dictionary with option texts and objects
|
boolean |
isRandomizable()
Gets whether this learner needs a random seed.
|
void |
resetLearningImpl()
Resets this classifier.
|
void |
trainOnInstanceImpl(MultiLabelInstance x) |
getPredictionForInstance, getPredictionForInstance, getVotesForInstance, trainOnInstanceImpl
contextIsCompatible, copy, correctlyClassifies, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getDownSampleRatio, getModel, getModelContext, getModelMeasurements, getNominalValueString, 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, prepareForUse, prepareForUse
getDescription, measureByteSize
getAWTRenderer
public String getPurposeString()
AbstractOptionHandler
getPurposeString
in interface OptionHandler
getPurposeString
in class AbstractClassifier
public void resetLearningImpl()
AbstractClassifier
resetLearningImpl
in class AbstractClassifier
public void trainOnInstanceImpl(MultiLabelInstance x)
trainOnInstanceImpl
in interface MultiLabelLearner
trainOnInstanceImpl
in class AbstractMultiLabelLearner
public Prediction getPredictionForInstance(MultiLabelInstance x)
getPredictionForInstance
in interface MultiLabelLearner
getPredictionForInstance
in class AbstractMultiLabelLearner
protected Measurement[] getModelMeasurementsImpl()
AbstractClassifier
getModelMeasurementsImpl
in class AbstractClassifier
public boolean isRandomizable()
Learner
isRandomizable
in interface Learner<Example<Instance>>
public void getModelDescription(StringBuilder out, int indent)
AbstractClassifier
getModelDescription
in class AbstractClassifier
out
- the stringbuilder to add the descriptionindent
- the number of characters to indentCopyright © 2019 University of Waikato, Hamilton, NZ. All Rights Reserved.