public class HeterogeneousEnsembleBlastFadingFactors extends HeterogeneousEnsembleAbstract implements MultiClassClassifier
Given a set of (heterogeneous) classifiers, BLAST builds an ensemble, and determines the weights of all ensemble members based on their performance on recent observed instances. This implementation uses fading factors, to emphasize the importance of recent predictions and fade away old predictions.
J. N. van Rijn, G. Holmes, B. Pfahringer, J. Vanschoren. Having a Blast: Meta-Learning and Heterogeneous Ensembles for Data Streams. In 2015 IEEE International Conference on Data Mining, pages 1003-1008. IEEE, 2015.
Parameters:
Modifier and Type | Field and Description |
---|---|
FloatOption |
alphaOption |
activeClassifiersOption, baselearnersOption, ensemble, gracePerionOption, historyTotal, instancesSeen, weightClassifiersOption
classifierRandom, modelContext, randomSeed, randomSeedOption, trainingWeightSeenByModel
config
Constructor and Description |
---|
HeterogeneousEnsembleBlastFadingFactors() |
Modifier and Type | Method and Description |
---|---|
void |
resetLearningImpl()
Resets this classifier.
|
void |
trainOnInstanceImpl(Instance inst)
Trains this classifier incrementally using the given instance.
The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods. |
getEnsembleSize, getMemberCliString, getModelDescription, getModelMeasurementsImpl, getPurposeString, getVotesForInstance, isRandomizable, maxIndex, normalize, prepareForUseImpl, setModelContext, topK
contextIsCompatible, copy, correctlyClassifies, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getModel, getModelContext, getModelMeasurements, getNominalValueString, getPredictionForInstance, getPredictionForInstance, getSubClassifiers, getSublearners, getVotesForInstance, modelAttIndexToInstanceAttIndex, modelAttIndexToInstanceAttIndex, resetLearning, setRandomSeed, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance, trainOnInstance
getCLICreationString, getOptions, getPreparedClassOption, prepareClassOptions, prepareForUse, prepareForUse
copy, measureByteSize, measureByteSize, toString
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
getCLICreationString, getOptions, prepareForUse, prepareForUse
measureByteSize
public FloatOption alphaOption
public HeterogeneousEnsembleBlastFadingFactors()
public void resetLearningImpl()
AbstractClassifier
resetLearningImpl
in class AbstractClassifier
public void trainOnInstanceImpl(Instance inst)
AbstractClassifier
trainOnInstanceImpl
in class AbstractClassifier
inst
- the instance to be used for trainingCopyright © 2019 University of Waikato, Hamilton, NZ. All Rights Reserved.