public class BasicMultiTargetRegressor extends AbstractMultiLabelLearner implements MultiTargetRegressor
Modifier and Type | Field and Description |
---|---|
ClassOption |
baseLearnerOption |
protected Classifier[] |
ensemble |
protected boolean |
hasStarted |
protected InstancesHeader[] |
header |
IntOption |
randomSeedOption |
classifierRandom, downSampleRatio, modelContext, randomSeed, trainingWeightSeenByModel
config
Constructor and Description |
---|
BasicMultiTargetRegressor() |
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 instance) |
protected void |
init() |
boolean |
isRandomizable()
Gets whether this learner needs a random seed.
|
void |
resetLearningImpl()
Resets this classifier.
|
void |
trainOnInstanceImpl(MultiLabelInstance instance) |
protected Instance |
transformInstance(MultiLabelInstance inst,
int outputIndex) |
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 randomSeedOption
public ClassOption baseLearnerOption
protected Classifier[] ensemble
protected boolean hasStarted
protected InstancesHeader[] header
protected void init()
public void resetLearningImpl()
AbstractClassifier
resetLearningImpl
in class AbstractClassifier
public void trainOnInstanceImpl(MultiLabelInstance instance)
trainOnInstanceImpl
in interface MultiLabelLearner
trainOnInstanceImpl
in class AbstractMultiLabelLearner
protected Instance transformInstance(MultiLabelInstance inst, int outputIndex)
public boolean isRandomizable()
Learner
isRandomizable
in interface Learner<Example<Instance>>
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 Prediction getPredictionForInstance(MultiLabelInstance instance)
getPredictionForInstance
in interface MultiLabelLearner
getPredictionForInstance
in class AbstractMultiLabelLearner
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