public class AdaptiveModelRulesModel extends AbstractRegressor implements Regressor
streamHeader
Constructor and Description |
---|
AdaptiveModelRulesModel(AdaptiveModelRulesModel model) |
AdaptiveModelRulesModel(String modelName) |
Modifier and Type | Method and Description |
---|---|
void |
getDescription(StringBuilder stringBuilder,
int i) |
int |
getNoOfFeatures() |
Object[] |
getPrediction(double[] cepEvent) |
void |
init(int noOfAttributes)
Initialize the model with input stream definition.
|
boolean |
isInitialized() |
boolean |
isValidStreamHeader(int noOfFeatures) |
protected void |
prepareForUseImpl(moa.tasks.TaskMonitor taskMonitor,
moa.core.ObjectRepository objectRepository) |
void |
setConfigurations(double splitConfidence,
double tieBreakThreshold,
int gracePeriod,
int changeDetector,
int anomalyDetector) |
double |
trainOnEvent(double[] cepEvent) |
createMOAInstance, generateHeader
copy, getCLICreationString, getOptions, getPreparedClassOption, getPurposeString, prepareClassOptions, prepareForUse, prepareForUse
public AdaptiveModelRulesModel(String modelName)
public AdaptiveModelRulesModel(AdaptiveModelRulesModel model)
public void getDescription(StringBuilder stringBuilder, int i)
getDescription
in interface moa.MOAObject
public void init(int noOfAttributes)
noOfAttributes
- number of attributes including features and targetpublic double trainOnEvent(double[] cepEvent)
trainOnEvent
in interface Regressor
cepEvent
- event datapublic Object[] getPrediction(double[] cepEvent)
getPrediction
in interface Regressor
public boolean isInitialized()
public boolean isValidStreamHeader(int noOfFeatures)
public void setConfigurations(double splitConfidence, double tieBreakThreshold, int gracePeriod, int changeDetector, int anomalyDetector)
public int getNoOfFeatures()
protected void prepareForUseImpl(moa.tasks.TaskMonitor taskMonitor, moa.core.ObjectRepository objectRepository)
prepareForUseImpl
in class moa.options.AbstractOptionHandler
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