weka.classifiers

Class AggregateableEvaluation

java.lang.Object

weka.classifiers.Evaluation

weka.classifiers.AggregateableEvaluation

All Implemented Interfaces:

Serializable, RevisionHandler, Summarizable

public class AggregateableEvaluation
extends Evaluation

Subclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object.

Version:

$Revision: 8034 $

Author:

Mark Hall (mhall{[at]}pentaho{[dot]}com)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
AggregateableEvaluation(Evaluation eval) Constructs a new AggregateableEvaluation object based on an Evaluation object
AggregateableEvaluation(Instances data) Constructs a new AggregateableEvaluation object
AggregateableEvaluation(Instances data, CostMatrix costMatrix) Constructs a new AggregateableEvaluation object

Method Summary

Methods

Modifier and Type	Method and Description
void	aggregate(Evaluation evaluation) Adds the statistics encapsulated in the supplied Evaluation object into this one.

Methods inherited from class weka.classifiers.Evaluation

areaUnderPRC, areaUnderROC, avgCost, confusionMatrix, correct, correlationCoefficient, coverageOfTestCasesByPredictedRegions, crossValidateModel, crossValidateModel, equals, errorRate, evaluateModel, evaluateModel, evaluateModel, evaluateModelOnce, evaluateModelOnce, evaluateModelOnce, evaluateModelOnceAndRecordPrediction, evaluateModelOnceAndRecordPrediction, evaluationForSingleInstance, falseNegativeRate, falsePositiveRate, fMeasure, getClassPriors, getDiscardPredictions, getHeader, getRevision, incorrect, kappa, KBInformation, KBMeanInformation, KBRelativeInformation, main, meanAbsoluteError, meanPriorAbsoluteError, numFalseNegatives, numFalsePositives, numInstances, numTrueNegatives, numTruePositives, pctCorrect, pctIncorrect, pctUnclassified, precision, predictions, priorEntropy, recall, relativeAbsoluteError, rootMeanPriorSquaredError, rootMeanSquaredError, rootRelativeSquaredError, setDiscardPredictions, setPriors, SFEntropyGain, SFMeanEntropyGain, SFMeanPriorEntropy, SFMeanSchemeEntropy, SFPriorEntropy, SFSchemeEntropy, sizeOfPredictedRegions, toClassDetailsString, toClassDetailsString, toCumulativeMarginDistributionString, toMatrixString, toMatrixString, toSummaryString, toSummaryString, toSummaryString, totalCost, trueNegativeRate, truePositiveRate, unclassified, unweightedMacroFmeasure, unweightedMicroFmeasure, updatePriors, useNoPriors, weightedAreaUnderPRC, weightedAreaUnderROC, weightedFalseNegativeRate, weightedFalsePositiveRate, weightedFMeasure, weightedPrecision, weightedRecall, weightedTrueNegativeRate, weightedTruePositiveRate, wekaStaticWrapper

Methods inherited from class java.lang.Object

getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

AggregateableEvaluation

public AggregateableEvaluation(Instances data)
                        throws Exception

Constructs a new AggregateableEvaluation object

Parameters:

data - the Instances to use

Throws:

Exception - if a problem occurs

AggregateableEvaluation

public AggregateableEvaluation(Instances data,
                       CostMatrix costMatrix)
                        throws Exception

Constructs a new AggregateableEvaluation object

Parameters:

data - the Instances to use

costMatrix - the cost matrix to use

Throws:

Exception - if a problem occurs

AggregateableEvaluation

public AggregateableEvaluation(Evaluation eval)
                        throws Exception

Constructs a new AggregateableEvaluation object based on an Evaluation object

Parameters:

evaluation - the Evaluation object to use

Throws:

Exception

Method Detail

aggregate

public void aggregate(Evaluation evaluation)

Adds the statistics encapsulated in the supplied Evaluation object into this one. Does not perform any checks for compatibility between the supplied Evaluation object and this one.

Parameters:

evaluation - the evaluation object to aggregate