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## Uses of Class
de.jstacs.results.NumericalResultSet

Packages that use NumericalResultSet
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

Methods in de.jstacs.classifiers that return NumericalResultSet
`NumericalResultSet` | `MappingClassifier.getNumericalCharacteristics()`
`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

Methods in de.jstacs.classifiers.differentiableSequenceScoreBased that return NumericalResultSet
`NumericalResultSet` | `ScoreClassifier.getNumericalCharacteristics()`

Uses of NumericalResultSet in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling

Methods in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling that return NumericalResultSet
`NumericalResultSet` | `SamplingScoreBasedClassifier.getNumericalCharacteristics()`

Uses of NumericalResultSet in de.jstacs.classifiers.performanceMeasures

Methods in de.jstacs.classifiers.performanceMeasures that return NumericalResultSet
`NumericalResultSet` | `SensitivityForFixedSpecificity.compute(double[][][] classSpecificScores)`
`NumericalResultSet` | `PositivePredictiveValueForFixedSensitivity.compute(double[][][] classSpecificScores)`
`NumericalResultSet` | `NumericalPerformanceMeasure.compute(double[][][] classSpecificScores)` This method allows to compute the performance measure of given class specific scores.
`NumericalResultSet` | `MaximumNumericalTwoClassMeasure.compute(double[][][] classSpecificScores)`
`NumericalResultSet` | `FalsePositiveRateForFixedSensitivity.compute(double[][][] classSpecificScores)`
`NumericalResultSet` | `ClassificationRate.compute(double[][][] classSpecificScores)`
`NumericalResultSet` | `AucROC.compute(double[][][] classSpecificScores)`
`NumericalResultSet` | `AucPR.compute(double[][][] classSpecificScores)`
`NumericalResultSet` | `SensitivityForFixedSpecificity.compute(double[] sortedScoresClass0, double[] sortedScoresClass1)`
`NumericalResultSet` | `PositivePredictiveValueForFixedSensitivity.compute(double[] sortedScoresClass0, double[] sortedScoresClass1)`
`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)`
`NumericalResultSet` | `FalsePositiveRateForFixedSensitivity.compute(double[] sortedScoresClass0, double[] sortedScoresClass1)`
`NumericalResultSet` | `ClassificationRate.compute(double[] sortedScoresClass0, double[] sortedScoresClass1)`
`NumericalResultSet` | `AucROC.compute(double[] sortedScoresClass0, double[] sortedScoresClass1)`
`NumericalResultSet` | `AucPR.compute(double[] sortedScoresClass0, double[] sortedScoresClass1)`

Uses of NumericalResultSet in de.jstacs.classifiers.trainSMBased

Methods in de.jstacs.classifiers.trainSMBased that return NumericalResultSet
`NumericalResultSet` | `TrainSMBasedClassifier.getNumericalCharacteristics()`

Uses of NumericalResultSet in de.jstacs.results

Subclasses of NumericalResultSet in de.jstacs.results
`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
`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
`void` | `MeanResultSet.addResults(NumericalResultSet... rs)` Adds `NumericalResultSet`s to this `MeanResultSet`.

Uses of NumericalResultSet in de.jstacs.sequenceScores

Methods in de.jstacs.sequenceScores that return NumericalResultSet
`NumericalResultSet` | `SequenceScore.getNumericalCharacteristics()` Returns the subset of numerical values that are also returned by `SequenceScore.getCharacteristics()`.

Uses of NumericalResultSet in de.jstacs.sequenceScores.differentiable

Methods in de.jstacs.sequenceScores.differentiable that return NumericalResultSet
`NumericalResultSet` | `AbstractDifferentiableSequenceScore.getNumericalCharacteristics()`

Uses of NumericalResultSet in de.jstacs.sequenceScores.statisticalModels.trainable

Methods in de.jstacs.sequenceScores.statisticalModels.trainable that return NumericalResultSet
`NumericalResultSet` | `VariableLengthWrapperTrainSM.getNumericalCharacteristics()`
`NumericalResultSet` | `UniformTrainSM.getNumericalCharacteristics()`
`NumericalResultSet` | `DifferentiableStatisticalModelWrapperTrainSM.getNumericalCharacteristics()`
`NumericalResultSet` | `CompositeTrainSM.getNumericalCharacteristics()`

Uses of NumericalResultSet in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous that return NumericalResultSet
`NumericalResultSet` | `HomogeneousTrainSM.getNumericalCharacteristics()`

Uses of NumericalResultSet in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous that return NumericalResultSet
`NumericalResultSet` | `DAGTrainSM.getNumericalCharacteristics()`

Uses of NumericalResultSet in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models that return NumericalResultSet
`NumericalResultSet` | `HigherOrderHMM.getNumericalCharacteristics()`

Uses of NumericalResultSet in de.jstacs.sequenceScores.statisticalModels.trainable.mixture

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.mixture that return NumericalResultSet
`NumericalResultSet` | `AbstractMixtureTrainSM.getNumericalCharacteristics()`

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