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## Uses of Class
de.jstacs.NotTrainedException

Packages that use NotTrainedException
de.jstacs.classifier | This package provides the framework for any classifier.
de.jstacs.classifier.scoringFunctionBased | Provides the classes for `Classifier`s that are based on `ScoringFunction`s.
de.jstacs.models | Provides the interface `Model` and its abstract implementation `AbstractModel`, which is the super class of all other models.
de.jstacs.models.discrete |
de.jstacs.models.discrete.homogeneous |
de.jstacs.models.discrete.inhomogeneous | This package contains various inhomogeneous models.
de.jstacs.models.discrete.inhomogeneous.shared |
de.jstacs.models.mixture | This package is the super package for any mixture model.
de.jstacs.models.utils |

Uses of NotTrainedException in de.jstacs.classifier

Methods in de.jstacs.classifier that throw NotTrainedException
`protected void` | `AbstractScoreBasedClassifier.check(Sample s)` This method checks if the given `Sample` 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.classifier.scoringFunctionBased

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

Uses of NotTrainedException in de.jstacs.models

Methods in de.jstacs.models that throw NotTrainedException
`Sample` | `Model.emitSample(int numberOfSequences, int... seqLength)` This method returns a `Sample` object containing artificial sequence(s).
`Sample` | `AbstractModel.emitSample(int numberOfSequences, int... seqLength)`
`double` | `NormalizableScoringFunctionModel.getLogProbFor(Sequence sequence, int startpos, int endpos)`
`double` | `CompositeModel.getLogProbFor(Sequence sequence, int startpos, int endpos)`
`double` | `Model.getProbFor(Sequence sequence)` Returns the probability of the given sequence given the model.
`double` | `AbstractModel.getProbFor(Sequence sequence)`
`double` | `Model.getProbFor(Sequence sequence, int startpos)` Returns the probability of (a part of) the given sequence given the model.
`double` | `AbstractModel.getProbFor(Sequence sequence, int startpos)`
`double` | `VariableLengthWrapperModel.getProbFor(Sequence sequence, int startpos, int endpos)`
`double` | `NormalizableScoringFunctionModel.getProbFor(Sequence sequence, int startpos, int endpos)`
`double` | `Model.getProbFor(Sequence sequence, int startpos, int endpos)` Returns the probability of (a part of) the given sequence given the model.
`double` | `CompositeModel.getProbFor(Sequence sequence, int startpos, int endpos)`

Uses of NotTrainedException in de.jstacs.models.discrete

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

Uses of NotTrainedException in de.jstacs.models.discrete.homogeneous

Methods in de.jstacs.models.discrete.homogeneous that throw NotTrainedException
`protected void` | `HomogeneousModel.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`.
`Sample` | `HomogeneousModel.emitSample(int no, int... length)` Creates a `Sample` of a given number of `Sequence`s from a trained homogeneous model.
`double` | `HomogeneousModel.getLogProbFor(Sequence sequence, int startpos, int endpos)`
`double` | `HomogeneousModel.getProbFor(Sequence sequence, int startpos, int endpos)`

Uses of NotTrainedException in de.jstacs.models.discrete.inhomogeneous

Methods in de.jstacs.models.discrete.inhomogeneous that throw NotTrainedException
`protected void` | `InhomogeneousDGM.check(Sequence sequence, int startpos, int endpos)`
`Sample` | `DAGModel.emitSample(int n, int... lengths)`
`double` | `DAGModel.getLogProbFor(Sequence sequence, int startpos, int endpos)`
`double` | `DAGModel.getProbFor(Sequence sequence, int startpos, int endpos)`
`abstract String` | `InhomogeneousDGM.getStructure()` Returns a `String` representation of the underlying graph.
`String` | `DAGModel.getStructure()`

Uses of NotTrainedException in de.jstacs.models.discrete.inhomogeneous.shared

Methods in de.jstacs.models.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.models.mixture

Methods in de.jstacs.models.mixture that throw NotTrainedException
`protected Sequence[]` | `StrandModel.emitSampleUsingCurrentParameterSet(int n, int... lengths)`
`double` | `AbstractMixtureModel.getScoreForBestRun()` Returns the value of the optimized function from the best run of the last training.

Uses of NotTrainedException in de.jstacs.models.utils

Methods in de.jstacs.models.utils that throw NotTrainedException
`static Sample` | `DiscreteInhomogenousSampleEmitter.emitSample(Model m, int n)` This method emits a sample with `n`sequences from the discrete inhomogeneous model `m` .``

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