public class PairedLearners extends AbstractClassifier implements MultiClassClassifier
Stephen H. Bach, Marcus A. Maloof, "Paired Learners for Concept Drift", Eighth IEEE International Conference on Data Mining (ICDM), 2008, pp.23-32
Modifier and Type | Field and Description |
---|---|
protected int[] |
c |
protected int |
changeDetected |
protected int |
i |
protected Instance[] |
instances |
protected int |
numberOfErrors |
protected Classifier |
reactiveLearner |
ClassOption |
reactiveLearnerOption |
protected Classifier |
stableLearner |
ClassOption |
stableLearnerOption |
protected int |
t |
protected int |
theta |
FloatOption |
thresholdOption |
protected int |
w |
IntOption |
windowSizeOption |
classifierRandom, modelContext, randomSeed, randomSeedOption, trainingWeightSeenByModel
config
Constructor and Description |
---|
PairedLearners() |
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. |
double[] |
getVotesForInstance(Instance inst)
Predicts the class memberships for a given instance.
|
boolean |
isRandomizable()
Gets whether this learner needs a random seed.
|
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. |
contextIsCompatible, copy, correctlyClassifies, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getModel, getModelContext, getModelMeasurements, getNominalValueString, getPredictionForInstance, getPredictionForInstance, getPurposeString, getSubClassifiers, getSublearners, getVotesForInstance, modelAttIndexToInstanceAttIndex, modelAttIndexToInstanceAttIndex, prepareForUseImpl, resetLearning, setModelContext, 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 ClassOption stableLearnerOption
public ClassOption reactiveLearnerOption
public IntOption windowSizeOption
public FloatOption thresholdOption
protected int[] c
protected Classifier stableLearner
protected Classifier reactiveLearner
protected int t
protected int w
protected int theta
protected Instance[] instances
protected int changeDetected
protected int numberOfErrors
protected int i
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 trainingpublic double[] getVotesForInstance(Instance inst)
Classifier
getVotesForInstance
in interface Classifier
getVotesForInstance
in class AbstractClassifier
inst
- the instance to be classifiedpublic 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 indentCopyright © 2019 University of Waikato, Hamilton, NZ. All Rights Reserved.