public class OzaBagASHT extends AbstractClassifier implements MultiClassClassifier
OzaBagASHT -l ASHoeffdingTree -s 10 -u -r
Parameters:OzaBag
Modifier and Type | Field and Description |
---|---|
protected double |
alpha |
ClassOption |
baseLearnerOption |
protected ASHoeffdingTree[] |
ensemble |
IntOption |
ensembleSizeOption |
protected double[] |
error |
IntOption |
firstClassifierSizeOption |
FlagOption |
resetTreesOption |
FlagOption |
useWeightOption |
classifierRandom, downSampleRatio, modelContext, randomSeed, randomSeedOption, trainingWeightSeenByModel
config
Constructor and Description |
---|
OzaBagASHT() |
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. |
String |
getPurposeString()
Dictionary with option texts and objects
|
Classifier[] |
getSubClassifiers()
Gets the classifiers of this ensemble.
|
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, getDownSampleRatio, getModel, getModelContext, getModelMeasurements, getNominalValueString, getPredictionForInstance, getPredictionForInstance, 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
getCLICreationString, getOptions, prepareForUse, prepareForUse
measureByteSize
public IntOption ensembleSizeOption
public IntOption firstClassifierSizeOption
public FlagOption useWeightOption
public FlagOption resetTreesOption
public ClassOption baseLearnerOption
protected ASHoeffdingTree[] ensemble
protected double[] error
protected double alpha
public String getPurposeString()
AbstractOptionHandler
getPurposeString
in interface OptionHandler
getPurposeString
in class AbstractClassifier
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 void getModelDescription(StringBuilder out, int indent)
AbstractClassifier
getModelDescription
in class AbstractClassifier
out
- the stringbuilder to add the descriptionindent
- the number of characters to indentpublic boolean isRandomizable()
Learner
isRandomizable
in interface Learner<Example<Instance>>
protected Measurement[] getModelMeasurementsImpl()
AbstractClassifier
getModelMeasurementsImpl
in class AbstractClassifier
public Classifier[] getSubClassifiers()
Classifier
getSubClassifiers
in interface Classifier
getSubClassifiers
in class AbstractClassifier
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