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## Uses of Class
de.jstacs.NotTrainedException

Packages that use NotTrainedException
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.sequenceScores.statisticalModels | Provides all `StatisticalModel`s, which can compute a proper (i.e., normalized) likelihood over the input space of sequences.
de.jstacs.sequenceScores.statisticalModels.differentiable | Provides all `DifferentiableStatisticalModel`s, which can compute the gradient with respect to their parameters for a given input `Sequence`.
de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels | Provides `DifferentiableStatisticalModel`s that are directed graphical models.
de.jstacs.sequenceScores.statisticalModels.trainable | Provides all `TrainableStatisticalModel`s, which can be learned from a single `DataSet`.
de.jstacs.sequenceScores.statisticalModels.trainable.discrete |
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.discrete.inhomogeneous.shared |
de.jstacs.sequenceScores.statisticalModels.trainable.mixture | This package is the super package for any mixture model.
de.jstacs.utils | This package contains a bundle of useful classes and interfaces like ...

Uses of NotTrainedException in de.jstacs.classifiers

Methods in de.jstacs.classifiers that throw NotTrainedException
`protected void` | `AbstractScoreBasedClassifier.check(DataSet s)` This method checks if the given `DataSet` can be used.
`protected void` | `AbstractScoreBasedClassifier.check(Sequence seq)` This method checks if the given `Sequence` can be used.
`protected double` | `MappingClassifier.getScore(Sequence seq, int i, boolean check)`
`protected abstract double` | `AbstractScoreBasedClassifier.getScore(Sequence seq, int i, boolean check)` This method returns the score for a given `Sequence` and a given class.

Uses of NotTrainedException in de.jstacs.classifiers.differentiableSequenceScoreBased

Methods in de.jstacs.classifiers.differentiableSequenceScoreBased that throw NotTrainedException
`protected double` | `ScoreClassifier.getScore(Sequence seq, int i, boolean check)`

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

Methods in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling that throw NotTrainedException
`protected double` | `SamplingScoreBasedClassifier.getScore(Sequence seq, int cls, boolean check)`

Uses of NotTrainedException in de.jstacs.sequenceScores.statisticalModels

Methods in de.jstacs.sequenceScores.statisticalModels that throw NotTrainedException
`DataSet` | `StatisticalModel.emitDataSet(int numberOfSequences, int... seqLength)` This method returns a `DataSet` object containing artificial sequence(s).

Uses of NotTrainedException in de.jstacs.sequenceScores.statisticalModels.differentiable

Methods in de.jstacs.sequenceScores.statisticalModels.differentiable that throw NotTrainedException
`DataSet` | `UniformDiffSM.emitDataSet(int numberOfSequences, int... seqLength)`
`DataSet` | `IndependentProductDiffSM.emitDataSet(int numberOfSequences, int... seqLength)`
`DataSet` | `AbstractDifferentiableStatisticalModel.emitDataSet(int numberOfSequences, int... seqLength)`

Uses of NotTrainedException in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels

Methods in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels that throw NotTrainedException
`DataSet` | `BayesianNetworkDiffSM.emitDataSet(int numberOfSequences, int... seqLength)`

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

Methods in de.jstacs.sequenceScores.statisticalModels.trainable that throw NotTrainedException
`protected void` | `AbstractTrainableStatisticalModel.check(Sequence sequence, int startpos, int endpos)` This method checks all parameters before a probability can be computed for a sequence.
`DataSet` | `AbstractTrainableStatisticalModel.emitDataSet(int numberOfSequences, int... seqLength)`
`double` | `VariableLengthWrapperTrainSM.getLogProbFor(Sequence sequence, int startpos, int endpos)`
`double` | `DifferentiableStatisticalModelWrapperTrainSM.getLogProbFor(Sequence sequence, int startpos, int endpos)`
`double` | `CompositeTrainSM.getLogProbFor(Sequence sequence, int startpos, int endpos)`

Uses of NotTrainedException in de.jstacs.sequenceScores.statisticalModels.trainable.discrete

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete that throw NotTrainedException
`protected void` | `DiscreteGraphicalTrainSM.check(Sequence sequence, int startpos, int endpos)` Checks some conditions on a `Sequence`.

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

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous that throw NotTrainedException
`protected void` | `HomogeneousTrainSM.check(Sequence sequence, int startpos, int endpos)` Checks some constraints, these are in general conditions on the `AlphabetContainer` of a (sub)`Sequence` between `startpos` und `endpos`.
`DataSet` | `HomogeneousTrainSM.emitDataSet(int no, int... length)` Creates a `DataSet` of a given number of `Sequence`s from a trained homogeneous model.
`double` | `HomogeneousTrainSM.getLogProbFor(Sequence sequence, int startpos, int endpos)`

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

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous that throw NotTrainedException
`protected void` | `InhomogeneousDGTrainSM.check(Sequence sequence, int startpos, int endpos)`
`DataSet` | `DAGTrainSM.emitDataSet(int n, int... lengths)`
`double` | `DAGTrainSM.getLogProbFor(Sequence sequence, int startpos, int endpos)`
`abstract String` | `InhomogeneousDGTrainSM.getStructure()` Returns a `String` representation of the underlying graph.
`String` | `DAGTrainSM.getStructure()`

Uses of NotTrainedException in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared that throw NotTrainedException
`String` | `SharedStructureMixture.getStructure()` Returns a `String` representation of the structure of the used models.

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

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.mixture that throw NotTrainedException
`protected Sequence[]` | `StrandTrainSM.emitDataSetUsingCurrentParameterSet(int n, int... lengths)`
`double` | `AbstractMixtureTrainSM.getScoreForBestRun()` Returns the value of the optimized function from the best run of the last training.

Uses of NotTrainedException in de.jstacs.utils

Methods in de.jstacs.utils that throw NotTrainedException
`static DataSet` | `DiscreteInhomogenousDataSetEmitter.emitDataSet(StatisticalModel m, int n)` This method emits a sample with `n`sequences from the discrete inhomogeneous model `m` .``

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