com.rapidminer.operator.learner.meta
Class BayBoostStream

java.lang.Object
  com.rapidminer.tools.AbstractObservable<Operator>
      com.rapidminer.operator.Operator
          com.rapidminer.operator.OperatorChain
              com.rapidminer.operator.learner.meta.AbstractMetaLearner
                  com.rapidminer.operator.learner.meta.BayBoostStream

All Implemented Interfaces:

ConfigurationListener, PreviewListener, ResourceConsumer, CapabilityProvider, Learner, ParameterHandler, LoggingHandler, Observable<Operator>

public class BayBoostStream
extends AbstractMetaLearner

Assumptions:

1. target label is always boolean
2. goal is to fit a crisp ensemble classifier (use_distribution always off)
3. base classifier weights are always adapted by a single row from first to last
4. no internal bootstrapping

Author:

Martin Scholz

Nested Class Summary

static class

BayBoostStream.BatchFilterCondition Class that filters an ExampleSet by the value of a special attribute.

Field Summary

static double	MIN_ADVANTAGE Discard models with an advantage of less than the specified value.
static double	MIN_LIFT_RATIO_SOFT_CLASSIFIER The probabilistic prediction of soft classifiers is restricted, similar to a confidence bound.
static java.lang.String	PARAMETER_BATCH_SIZE Name of the variable specifying the maximal number of iterations of the learner.
static java.lang.String	PARAMETER_FRACTION_HOLD_OUT_SET Parameter name to activate a hold out set for tuning.
static java.lang.String	PARAMETER_RESCALE_LABEL_PRIORS Boolean parameter to specify whether the label priors should be equally likely after first iteration.
static java.lang.String	STREAM_CONTROL_ATTRIB_NAME Name of the special attribute with additional stream control information.

Fields inherited from class com.rapidminer.operator.learner.meta.AbstractMetaLearner

exampleSetInput, innerModelSink

Fields inherited from interface com.rapidminer.operator.learner.CapabilityProvider

PROPERTY_RAPIDMINER_GENERAL_CAPABILITIES_WARN

Constructor Summary

BayBoostStream(OperatorDescription description)
Constructor.

Method Summary

void	doWork() Overwrite to also return the performance (run-) vector
java.util.List<ParameterType>	getParameterTypes() Adds the parameters "rescale label priors" and "weighted batch size".
Model	learn(ExampleSet exampleSet) Constructs a Model repeatedly running a weak learner, reweighting the training example set accordingly, and combining the hypothesis using the available weighted performance values.
protected void	prepareWeights(ExampleSet exampleSet)
boolean	supportsCapability(OperatorCapability lc) Overrides the method of the super class.

Methods inherited from class com.rapidminer.operator.learner.meta.AbstractMetaLearner

applyInnerLearner, executeInnerLearner, getEstimatedPerformance, getInnerModelSink, getModelOutputPort, getTrainingSetInputPort, getWeights, modifyExampleSetMetaData, modifyGeneratedModelMetaData, shouldAutoConnect, shouldCalculateWeights, shouldEstimatePerformance

Methods inherited from class com.rapidminer.operator.OperatorChain

addOperator, addOperator, addSubprocess, areSubprocessesExtendable, assumePreconditionsSatisfied, checkDeprecations, checkIO, checkNumberOfInnerOperators, checkProperties, clear, clearAllInnerSinks, cloneOperator, collectErrors, createProcessTree, createSubprocess, freeMemory, getAllInnerOperators, getAllInnerOperatorsAndMe, getImmediateChildren, getIndexOfOperator, getInnerOperatorCondition, getMaxNumberOfInnerOperators, getMinNumberOfInnerOperators, getNumberOfAllOperators, getNumberOfOperators, getNumberOfSubprocesses, getOperator, getOperatorFromAll, getOperators, getSubprocess, getSubprocesses, isEnabled, lookupOperator, notifyRenaming, performAdditionalChecks, processFinished, processStarts, propagateDirtyness, registerOperator, removeOperator, removeSubprocess, shouldAddNonConsumedInput, shouldReturnInnerOutput, unregisterOperator, updateExecutionOrder, walk

Methods inherited from class com.rapidminer.operator.Operator

acceptsInput, addError, addError, addValue, addWarning, apply, apply, checkAll, checkAllExcludingMetaData, checkForStop, clearErrorList, createExperimentTree, createExperimentTree, createFromXML, createFromXML, createFromXML, createMarkedExperimentTree, createMarkedProcessTree, createProcessTree, disconnectPorts, execute, fireUpdate, getAddOnlyAdditionalOutput, getApplyCount, getCompatibilityLevel, getDeliveredOutputClasses, getDeprecationInfo, getDesiredInputClasses, getDOMRepresentation, getEncoding, getErrorList, getExecutionUnit, getExperiment, getIncompatibleVersionChanges, getInput, getInput, getInput, getInputClasses, getInputDescription, getInputPorts, getIODescription, getLog, getLogger, getName, getNumberOfBreakpoints, getOperatorClassName, getOperatorDescription, getOutputClasses, getOutputPorts, getParameter, getParameterAsBoolean, getParameterAsChar, getParameterAsColor, getParameterAsDouble, getParameterAsFile, getParameterAsFile, getParameterAsInputStream, getParameterAsInt, getParameterAsMatrix, getParameterAsRepositoryLocation, getParameterAsString, getParameterHandler, getParameterList, getParameters, getParameterTupel, getParameterType, getParent, getPortOwner, getProcess, getResourceConsumptionEstimator, getRoot, getStartTime, getTransformer, getUserDescription, getValue, getValues, getXML, getXML, getXML, hasBreakpoint, hasBreakpoint, hasInput, inApplyLoop, isDebugMode, isDirty, isExpanded, isParallel, isParameterSet, isRunning, log, log, logError, logNote, logWarning, makeDirty, makeDirtyOnUpdate, preAutoWire, producesOutput, register, remove, removeAndKeepConnections, rename, resume, setBreakpoint, setCompatibilityLevel, setEnabled, setEnclosingProcess, setExpanded, setInput, setListParameter, setPairParameter, setParameter, setParameters, setUserDescription, shouldAutoConnect, shouldStopStandaloneExecution, toString, transformMetaData, writeXML, writeXML

Methods inherited from class com.rapidminer.tools.AbstractObservable

addObserver, addObserverAsFirst, fireUpdate, removeObserver

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface com.rapidminer.operator.learner.Learner

getName

Field Detail

PARAMETER_BATCH_SIZE

public static final java.lang.String PARAMETER_BATCH_SIZE

Name of the variable specifying the maximal number of iterations of the learner.

See Also:

Constant Field Values

PARAMETER_RESCALE_LABEL_PRIORS

public static final java.lang.String PARAMETER_RESCALE_LABEL_PRIORS

Boolean parameter to specify whether the label priors should be equally likely after first iteration.

See Also:

Constant Field Values

PARAMETER_FRACTION_HOLD_OUT_SET

public static final java.lang.String PARAMETER_FRACTION_HOLD_OUT_SET

Parameter name to activate a hold out set for tuning.

See Also:

Constant Field Values

MIN_ADVANTAGE

public static final double MIN_ADVANTAGE

Discard models with an advantage of less than the specified value.

See Also:

Constant Field Values

STREAM_CONTROL_ATTRIB_NAME

public static final java.lang.String STREAM_CONTROL_ATTRIB_NAME

Name of the special attribute with additional stream control information.

See Also:

Constant Field Values

MIN_LIFT_RATIO_SOFT_CLASSIFIER

public static final double MIN_LIFT_RATIO_SOFT_CLASSIFIER

The probabilistic prediction of soft classifiers is restricted, similar to a confidence bound. If the lift is close to 0 it is replaced by the minimum lift below. Analogously a maximum lift value is defined by (1 / MIN_LIFT_RATIO_SOFT_CLASSIFIER).

See Also:

Constant Field Values

Constructor Detail

BayBoostStream

public BayBoostStream(OperatorDescription description)

Constructor.

Method Detail

supportsCapability

public boolean supportsCapability(OperatorCapability lc)

Overrides the method of the super class.

prepareWeights

protected void prepareWeights(ExampleSet exampleSet)

learn

public Model learn(ExampleSet exampleSet)
            throws OperatorException

Constructs a Model repeatedly running a weak learner, reweighting the training example set accordingly, and combining the hypothesis using the available weighted performance values.

Throws:

OperatorException

doWork

public void doWork()
            throws OperatorException

Overwrite to also return the performance (run-) vector

Overrides:

doWork in class AbstractMetaLearner

Throws:

OperatorException

getParameterTypes

public java.util.List<ParameterType> getParameterTypes()

Adds the parameters "rescale label priors" and "weighted batch size".

Specified by:

getParameterTypes in interface ParameterHandler

Overrides:

getParameterTypes in class Operator