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Packages that use NumericalResultSet | |
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de.jstacs.classifiers | This package provides the framework for any classifier. |
de.jstacs.classifiers.differentiableSequenceScoreBased | Provides the classes for Classifier s that are based on SequenceScore s. |
de.jstacs.classifiers.differentiableSequenceScoreBased.sampling | Provides the classes for AbstractScoreBasedClassifier s that are based on
SamplingDifferentiableStatisticalModel s
and that sample parameters using the Metropolis-Hastings algorithm. |
de.jstacs.classifiers.performanceMeasures | This package provides the implementations of performance measures that can be used to assess any classifier |
de.jstacs.classifiers.trainSMBased | Provides the classes for Classifier s that are based on TrainableStatisticalModel s |
de.jstacs.results | This package provides classes for results and sets of results. |
de.jstacs.sequenceScores | Provides all SequenceScore s, which can be used to score a Sequence , typically using some model assumptions. |
de.jstacs.sequenceScores.differentiable | |
de.jstacs.sequenceScores.statisticalModels.trainable | Provides all TrainableStatisticalModel s, which can
be learned from a single DataSet . |
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous | |
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous | This package contains various inhomogeneous models. |
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models | The package provides different implementations of hidden Markov models based on AbstractHMM |
de.jstacs.sequenceScores.statisticalModels.trainable.mixture | This package is the super package for any mixture model. |
Uses of NumericalResultSet in de.jstacs.classifiers |
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Methods in de.jstacs.classifiers that return NumericalResultSet | |
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NumericalResultSet |
MappingClassifier.getNumericalCharacteristics()
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abstract NumericalResultSet |
AbstractClassifier.getNumericalCharacteristics()
Returns the subset of numerical values that are also returned by AbstractClassifier.getCharacteristics() . |
Uses of NumericalResultSet in de.jstacs.classifiers.differentiableSequenceScoreBased |
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Methods in de.jstacs.classifiers.differentiableSequenceScoreBased that return NumericalResultSet | |
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NumericalResultSet |
ScoreClassifier.getNumericalCharacteristics()
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Uses of NumericalResultSet in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling |
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Methods in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling that return NumericalResultSet | |
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NumericalResultSet |
SamplingScoreBasedClassifier.getNumericalCharacteristics()
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Uses of NumericalResultSet in de.jstacs.classifiers.performanceMeasures |
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Methods in de.jstacs.classifiers.performanceMeasures that return NumericalResultSet | |
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NumericalResultSet |
SensitivityForFixedSpecificity.compute(double[][][] classSpecificScores)
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NumericalResultSet |
PositivePredictiveValueForFixedSensitivity.compute(double[][][] classSpecificScores)
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NumericalResultSet |
NumericalPerformanceMeasure.compute(double[][][] classSpecificScores)
This method allows to compute the performance measure of given class specific scores. |
NumericalResultSet |
MaximumNumericalTwoClassMeasure.compute(double[][][] classSpecificScores)
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NumericalResultSet |
FalsePositiveRateForFixedSensitivity.compute(double[][][] classSpecificScores)
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NumericalResultSet |
ClassificationRate.compute(double[][][] classSpecificScores)
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NumericalResultSet |
AucROC.compute(double[][][] classSpecificScores)
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NumericalResultSet |
AucPR.compute(double[][][] classSpecificScores)
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NumericalResultSet |
SensitivityForFixedSpecificity.compute(double[] sortedScoresClass0,
double[] sortedScoresClass1)
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NumericalResultSet |
PositivePredictiveValueForFixedSensitivity.compute(double[] sortedScoresClass0,
double[] sortedScoresClass1)
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NumericalResultSet |
NumericalPerformanceMeasure.compute(double[] sortedScoresClass0,
double[] sortedScoresClass1)
This method allows to compute the performance measure of given sorted score ratios. |
NumericalResultSet |
MaximumNumericalTwoClassMeasure.compute(double[] sortedScoresClass0,
double[] sortedScoresClass1)
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NumericalResultSet |
FalsePositiveRateForFixedSensitivity.compute(double[] sortedScoresClass0,
double[] sortedScoresClass1)
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NumericalResultSet |
ClassificationRate.compute(double[] sortedScoresClass0,
double[] sortedScoresClass1)
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NumericalResultSet |
AucROC.compute(double[] sortedScoresClass0,
double[] sortedScoresClass1)
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NumericalResultSet |
AucPR.compute(double[] sortedScoresClass0,
double[] sortedScoresClass1)
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Uses of NumericalResultSet in de.jstacs.classifiers.trainSMBased |
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Methods in de.jstacs.classifiers.trainSMBased that return NumericalResultSet | |
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NumericalResultSet |
TrainSMBasedClassifier.getNumericalCharacteristics()
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Uses of NumericalResultSet in de.jstacs.results |
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Subclasses of NumericalResultSet in de.jstacs.results | |
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class |
MeanResultSet
Class that computes the mean and the standard error of a series of NumericalResultSet s. |
Methods in de.jstacs.results that return NumericalResultSet | |
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NumericalResultSet |
MeanResultSet.getStatistics()
Returns the means and (if possible the) standard errors of the results in this MeanResultSet as a new NumericalResultSet . |
Methods in de.jstacs.results with parameters of type NumericalResultSet | |
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void |
MeanResultSet.addResults(NumericalResultSet... rs)
Adds NumericalResultSet s to this MeanResultSet . |
Uses of NumericalResultSet in de.jstacs.sequenceScores |
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Methods in de.jstacs.sequenceScores that return NumericalResultSet | |
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NumericalResultSet |
SequenceScore.getNumericalCharacteristics()
Returns the subset of numerical values that are also returned by SequenceScore.getCharacteristics() . |
Uses of NumericalResultSet in de.jstacs.sequenceScores.differentiable |
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Methods in de.jstacs.sequenceScores.differentiable that return NumericalResultSet | |
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NumericalResultSet |
AbstractDifferentiableSequenceScore.getNumericalCharacteristics()
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Uses of NumericalResultSet in de.jstacs.sequenceScores.statisticalModels.trainable |
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Methods in de.jstacs.sequenceScores.statisticalModels.trainable that return NumericalResultSet | |
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NumericalResultSet |
VariableLengthWrapperTrainSM.getNumericalCharacteristics()
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NumericalResultSet |
UniformTrainSM.getNumericalCharacteristics()
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NumericalResultSet |
DifferentiableStatisticalModelWrapperTrainSM.getNumericalCharacteristics()
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NumericalResultSet |
CompositeTrainSM.getNumericalCharacteristics()
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Uses of NumericalResultSet in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous |
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Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous that return NumericalResultSet | |
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NumericalResultSet |
HomogeneousTrainSM.getNumericalCharacteristics()
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Uses of NumericalResultSet in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous |
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Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous that return NumericalResultSet | |
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NumericalResultSet |
DAGTrainSM.getNumericalCharacteristics()
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Uses of NumericalResultSet in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models |
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Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models that return NumericalResultSet | |
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NumericalResultSet |
HigherOrderHMM.getNumericalCharacteristics()
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Uses of NumericalResultSet in de.jstacs.sequenceScores.statisticalModels.trainable.mixture |
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Methods in de.jstacs.sequenceScores.statisticalModels.trainable.mixture that return NumericalResultSet | |
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NumericalResultSet |
AbstractMixtureTrainSM.getNumericalCharacteristics()
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