com.rapidminer.operator.learner.meta
Class CostBasedThresholdLearner

java.lang.Object
  com.rapidminer.operator.Operator
      com.rapidminer.operator.OperatorChain
          com.rapidminer.operator.learner.meta.AbstractMetaLearner
              com.rapidminer.operator.learner.meta.CostBasedThresholdLearner

All Implemented Interfaces:

ConfigurationListener, PreviewListener, Learner, ParameterHandler, LoggingHandler

public class CostBasedThresholdLearner
extends AbstractMetaLearner

This operator uses a set of class weights and also allows a weight for the fact that an example is not classified at all (marked as unknown). Based on the predictions of the model of the inner learner this operator optimized a set of thresholds regarding the defined weights.

This operator might be very useful in cases where it is better to not classify an example then to classify it in a wrong way. This way, it is often possible to get very high accuracies for the remaining examples (which are actually classified) for the cost of having some examples which must still be manually classified.

Author:

Ingo Mierswa

Field Summary

static java.lang.String	PARAMETER_CLASS_WEIGHTS The parameter name for "The weights for all classes (first column: class names, second column: weight), empty: using 1 for all classes.
static java.lang.String	PARAMETER_LOCAL_RANDOM_SEED The parameter name for "Use the given random seed instead of global random numbers (-1: use global)"
static java.lang.String	PARAMETER_NUMBER_OF_ITERATIONS The parameter name for "Defines the number of optimization iterations.
static java.lang.String	PARAMETER_PREDICT_UNKNOWN_COSTS The parameter name for "Use this cost value for predicting an example as unknown (-1: use same costs as for correct class).
static java.lang.String	PARAMETER_TRAINING_RATIO The parameter name for "Use this amount of input data for model learning and the rest for threshold optimization.

Constructor Summary

CostBasedThresholdLearner(OperatorDescription description)

Method Summary

java.util.List<ParameterType>	getParameterTypes() Returns a list of ParameterTypes describing the parameters of this operator.
Model	learn(ExampleSet exampleSet) Trains a model.

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

apply, applyInnerLearner, getEstimatedPerformance, getInnerOperatorCondition, getInputClasses, getInputDescription, getMaxNumberOfInnerOperators, getMinNumberOfInnerOperators, getOutputClasses, getWeights, shouldCalculateWeights, shouldEstimatePerformance, supportsCapability

Methods inherited from class com.rapidminer.operator.OperatorChain

addAddListener, addOperator, addOperator, checkDeprecations, checkIO, checkNumberOfInnerOperators, checkProperties, clearErrorList, cloneOperator, createExperimentTree, createProcessTree, getAllInnerOperators, getIndexOfOperator, getInnerOperatorForName, getInnerOperatorsXML, getNumberOfAllOperators, getNumberOfOperators, getOperator, getOperatorFromAll, getOperators, performAdditionalChecks, processFinished, processStarts, registerOperator, removeAddListener, removeOperator, shouldAddNonConsumedInput, shouldReturnInnerOutput, unregisterOperator

Methods inherited from class com.rapidminer.operator.Operator

addError, addValue, addWarning, apply, checkForStop, createExperimentTree, createFromXML, createMarkedExperimentTree, createMarkedProcessTree, createProcessTree, getAddOnlyAdditionalOutput, getApplyCount, getDeliveredOutputClasses, getDeprecationInfo, getDesiredInputClasses, getEncoding, getErrorList, getExperiment, getInput, getInput, getInput, getIOContainerForInApplyLoopBreakpoint, getIODescription, getLog, getName, getOperatorClassName, getOperatorDescription, getParameter, getParameterAsBoolean, getParameterAsColor, getParameterAsDouble, getParameterAsFile, getParameterAsFile, getParameterAsInputStream, getParameterAsInt, getParameterAsMatrix, getParameterAsString, getParameterList, getParameters, getParameterType, getParent, getProcess, getStartTime, getStatus, getUserDescription, getValue, getValues, getXML, hasBreakpoint, hasBreakpoint, hasInput, inApplyLoop, isDebugMode, isEnabled, isExpanded, isParallel, isParameterSet, log, logError, logNote, logWarning, register, remove, rename, resume, setApplyCount, setBreakpoint, setEnabled, setExpanded, setInput, setListParameter, setOperatorParameters, setParameter, setParameters, setParent, setUserDescription, toString, writeXML

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_CLASS_WEIGHTS

public static final java.lang.String PARAMETER_CLASS_WEIGHTS

The parameter name for "The weights for all classes (first column: class names, second column: weight), empty: using 1 for all classes. The costs for not classifying at all are defined with class name '?'."

See Also:

Constant Field Values

PARAMETER_PREDICT_UNKNOWN_COSTS

public static final java.lang.String PARAMETER_PREDICT_UNKNOWN_COSTS

The parameter name for "Use this cost value for predicting an example as unknown (-1: use same costs as for correct class)."

See Also:

Constant Field Values

PARAMETER_TRAINING_RATIO

public static final java.lang.String PARAMETER_TRAINING_RATIO

The parameter name for "Use this amount of input data for model learning and the rest for threshold optimization."

See Also:

Constant Field Values

PARAMETER_NUMBER_OF_ITERATIONS

public static final java.lang.String PARAMETER_NUMBER_OF_ITERATIONS

The parameter name for "Defines the number of optimization iterations."

See Also:

Constant Field Values

PARAMETER_LOCAL_RANDOM_SEED

public static final java.lang.String PARAMETER_LOCAL_RANDOM_SEED

The parameter name for "Use the given random seed instead of global random numbers (-1: use global)"

See Also:

Constant Field Values

Constructor Detail

CostBasedThresholdLearner

public CostBasedThresholdLearner(OperatorDescription description)

Method Detail

learn

public Model learn(ExampleSet exampleSet)
            throws OperatorException

Description copied from interface: Learner

Trains a model. This method should be called by apply() and is implemented by subclasses.

Throws:

OperatorException

getParameterTypes

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

Description copied from class: Operator

Returns a list of ParameterTypes describing the parameters of this operator. The default implementation returns an empty list if no input objects can be retained and special parameters for those input objects which can be prevented from being consumed.

Specified by:

getParameterTypes in interface ParameterHandler

Overrides:

getParameterTypes in class Operator