Package weka.classifiers

Class StoppableEvaluation

java.lang.Object

weka.classifiers.Evaluation

weka.classifiers.StoppableEvaluation

All Implemented Interfaces:

Stoppable, StoppableWithFeedback, Serializable, weka.core.RevisionHandler, weka.core.Summarizable

public class StoppableEvaluation
extends weka.classifiers.Evaluation
implements StoppableWithFeedback

Extended Evaluation class that can stop its evaluation processes better.

Author:

fracpete (fracpete at waikato dot ac dot nz)

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.Evaluation

BUILT_IN_EVAL_METRICS, m_delegate

Constructor Summary

Constructors

Constructor	Description
StoppableEvaluation(weka.core.Instances data)	Initializes all the counters for the evaluation.
StoppableEvaluation(weka.core.Instances data, weka.classifiers.CostMatrix costMatrix)	Initializes all the counters for the evaluation and also takes a cost matrix as parameter.

Method Summary

Modifier and Type	Method	Description
boolean	isStopped()	Whether the execution has been stopped.
void	stopExecution()	Stops the execution.

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

Methods inherited from class java.lang.Object

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

Constructor Detail

StoppableEvaluation

public StoppableEvaluation(weka.core.Instances data)
                    throws Exception

Initializes all the counters for the evaluation. Use useNoPriors() if the dataset is the test set and you can't initialize with the priors from the training set via setPriors(Instances).

Parameters:

data - set of training instances, to get some header information and prior class distribution information

Throws:

Exception - if the class is not defined

See Also:

Evaluation.useNoPriors(), Evaluation.setPriors(Instances)

StoppableEvaluation

public StoppableEvaluation(weka.core.Instances data,
                           weka.classifiers.CostMatrix costMatrix)
                    throws Exception

Initializes all the counters for the evaluation and also takes a cost matrix as parameter. Use useNoPriors() if the dataset is the test set and you can't initialize with the priors from the training set via setPriors(Instances).

Parameters:

data - set of training instances, to get some header information and prior class distribution information

costMatrix - the cost matrix---if null, default costs will be used

Throws:

Exception - if cost matrix is not compatible with data, the class is not defined or the class is numeric

See Also:

Evaluation.useNoPriors(), Evaluation.setPriors(Instances)

Method Detail

stopExecution

public void stopExecution()

Stops the execution. No message set.

Specified by:

stopExecution in interface Stoppable

isStopped

public boolean isStopped()

Whether the execution has been stopped.

Specified by:

isStopped in interface StoppableWithFeedback

Returns:

true if stopped