Package weka.classifiers
Class AggregateableEvaluation
- java.lang.Object
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- weka.classifiers.Evaluation
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- weka.classifiers.AggregateableEvaluation
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- All Implemented Interfaces:
java.io.Serializable,RevisionHandler,Summarizable
public class AggregateableEvaluation extends Evaluation
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:
- Serialized Form
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Field Summary
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Fields inherited from class weka.classifiers.Evaluation
BUILT_IN_EVAL_METRICS
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Constructor Summary
Constructors Constructor Description AggregateableEvaluation(Evaluation eval)Constructs a new AggregateableEvaluation object based on an Evaluation objectAggregateableEvaluation(Instances data)Constructs a new AggregateableEvaluation objectAggregateableEvaluation(Instances data, CostMatrix costMatrix)Constructs a new AggregateableEvaluation object
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description voidaggregate(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 Detail
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AggregateableEvaluation
public AggregateableEvaluation(Instances data) throws java.lang.Exception
Constructs a new AggregateableEvaluation object- Parameters:
data- the Instances to use- Throws:
java.lang.Exception- if a problem occurs
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AggregateableEvaluation
public AggregateableEvaluation(Instances data, CostMatrix costMatrix) throws java.lang.Exception
Constructs a new AggregateableEvaluation object- Parameters:
data- the Instances to usecostMatrix- the cost matrix to use- Throws:
java.lang.Exception- if a problem occurs
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AggregateableEvaluation
public AggregateableEvaluation(Evaluation eval) throws java.lang.Exception
Constructs a new AggregateableEvaluation object based on an Evaluation object- Parameters:
eval- the Evaluation object to use- Throws:
java.lang.Exception
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Method Detail
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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
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