Package weka.classifiers
Class AggregateableEvaluation
java.lang.Object
weka.classifiers.Evaluation
weka.classifiers.AggregateableEvaluation
- All Implemented Interfaces:
Serializable
,RevisionHandler
,Summarizable
Subclass of Evaluation that provides a method for aggregating the results
stored in another Evaluation object. Delegates to the actual implementation
in weka.classifiers.evaluation.AggregateableEvaluation.
- Version:
- $Revision: 9320 $
- Author:
- Mark Hall (mhall{[at]}pentaho{[dot]}com)
- See Also:
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Field Summary
Fields inherited from class weka.classifiers.Evaluation
BUILT_IN_EVAL_METRICS
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Constructor Summary
ConstructorDescriptionConstructs a new AggregateableEvaluation object based on an Evaluation objectConstructs a new AggregateableEvaluation objectAggregateableEvaluation
(Instances data, CostMatrix costMatrix) Constructs a new AggregateableEvaluation object -
Method Summary
Modifier and TypeMethodDescriptionvoid
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, crossValidateModel, equals, errorRate, evaluateModel, evaluateModel, evaluateModel, evaluateModelOnce, evaluateModelOnce, evaluateModelOnce, evaluateModelOnceAndRecordPrediction, evaluateModelOnceAndRecordPrediction, evaluationForSingleInstance, falseNegativeRate, falsePositiveRate, fMeasure, getAllEvaluationMetricNames, getClassPriors, getDiscardPredictions, getHeader, getMetricsToDisplay, getPluginMetric, getPluginMetrics, getRevision, incorrect, kappa, KBInformation, KBMeanInformation, KBRelativeInformation, main, matthewsCorrelationCoefficient, meanAbsoluteError, meanPriorAbsoluteError, numFalseNegatives, numFalsePositives, numInstances, numTrueNegatives, numTruePositives, pctCorrect, pctIncorrect, pctUnclassified, precision, predictions, priorEntropy, recall, relativeAbsoluteError, rootMeanPriorSquaredError, rootMeanSquaredError, rootRelativeSquaredError, setDiscardPredictions, setMetricsToDisplay, setPriors, SFEntropyGain, SFMeanEntropyGain, SFMeanPriorEntropy, SFMeanSchemeEntropy, SFPriorEntropy, SFSchemeEntropy, sizeOfPredictedRegions, toClassDetailsString, toClassDetailsString, toCumulativeMarginDistributionString, toggleEvalMetrics, toMatrixString, toMatrixString, toSummaryString, toSummaryString, toSummaryString, totalCost, trueNegativeRate, truePositiveRate, unclassified, unweightedMacroFmeasure, unweightedMicroFmeasure, updatePriors, useNoPriors, weightedAreaUnderPRC, weightedAreaUnderROC, weightedFalseNegativeRate, weightedFalsePositiveRate, weightedFMeasure, weightedMatthewsCorrelation, weightedPrecision, weightedRecall, weightedTrueNegativeRate, weightedTruePositiveRate, wekaStaticWrapper
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Constructor Details
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AggregateableEvaluation
Constructs a new AggregateableEvaluation object- Parameters:
data
- the Instances to use- Throws:
Exception
- if a problem occurs
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AggregateableEvaluation
Constructs a new AggregateableEvaluation object- Parameters:
data
- the Instances to usecostMatrix
- the cost matrix to use- Throws:
Exception
- if a problem occurs
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AggregateableEvaluation
Constructs a new AggregateableEvaluation object based on an Evaluation object- Parameters:
eval
- the Evaluation object to use- Throws:
Exception
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Method Details
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aggregate
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
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