Accord.NET Framework

## ILikelihoodTaggerTInput Interface |

Common interface for generative observation sequence taggers. A sequence
tagger can predict the class label of each individual observation in a
input sequence vector.

Syntax

public interface ILikelihoodTagger<TInput> : ITransform<TInput[], double>, ICovariantTransform<TInput[], double>, ITransform, IScoreTagger<TInput>, ITagger<TInput>, IMultilabelClassifier<TInput[], int[]>, IClassifier<TInput[], int[]>, IClassifier, ITransform<TInput[], int[]>, ICovariantTransform<TInput[], int[]>

- TInput
- The data type for the input data. Default is double[].

The ILikelihoodTaggerTInput type exposes the following members.

Properties

Name | Description | |
---|---|---|

NumberOfClasses |
Gets or sets the number of classes expected and recognized by the classifier.
(Inherited from IClassifier.) | |

NumberOfInputs |
Gets or sets the number of inputs accepted by the model.
(Inherited from ITransform.) | |

NumberOfOutputs |
Gets or sets the number of outputs generated by the model.
(Inherited from ITransform.) |

Methods

Name | Description | |
---|---|---|

Decide(TInput) |
Computes a class-label decision for a given input.
(Inherited from IClassifierTInput, TClasses.) | |

Decide(TInput) |
Computes class-label decisions for each vector in the given input.
(Inherited from IClassifierTInput, TClasses.) | |

Decide(TInput, TClasses) |
Computes class-label decisions for each vector in the given input.
(Inherited from IClassifierTInput, TClasses.) | |

Decide(TInput, TClasses) |
Computes class-label decisions for the given input.
(Inherited from IMultilabelClassifierTInput, TClasses.) | |

LogLikelihood(TInput) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
| |

LogLikelihood(TInput) |
Predicts a the log-likelihood that the sequence vector
has been generated by this log-likelihood tagger.
| |

LogLikelihood(TInput, Int32) |
Predicts a the log-likelihood that the sequence vector
has been generated by this log-likelihood tagger.
| |

LogLikelihood(TInput, Double) |
Predicts a the log-likelihood that the sequence vector
has been generated by this log-likelihood tagger.
| |

LogLikelihood(TInput, Int32) | ||

LogLikelihood(TInput, Int32, Double) | ||

LogLikelihoods(TInput) |
Predicts a the log-likelihood for each of the observations in
the sequence vector assuming each of the possible states in the
tagger model.
| |

LogLikelihoods(TInput) |
Predicts a the log-likelihood for each of the observations in
the sequence vector assuming each of the possible states in the
tagger model.
| |

LogLikelihoods(TInput, Double) |
Predicts a the log-likelihood for each of the observations in
the sequence vector assuming each of the possible states in the
tagger model.
| |

LogLikelihoods(TInput, Int32) | ||

LogLikelihoods(TInput, Double) | ||

LogLikelihoods(TInput, Int32) | ||

LogLikelihoods(TInput, Int32, Double) | ||

LogLikelihoods(TInput, Int32, Double) | ||

Probabilities(TInput) |
Predicts a the probabilities for each of the observations in
the sequence vector assuming each of the possible states in the
tagger model.
| |

Probabilities(TInput) |
Predicts a the probabilities for each of the observations in
the sequence vector assuming each of the possible states in the
tagger model.
| |

Probabilities(TInput, Double) |
Predicts a the probabilities for each of the observations in
the sequence vector assuming each of the possible states in the
tagger model.
| |

Probabilities(TInput, Int32) | ||

Probabilities(TInput, Double) | ||

Probabilities(TInput, Int32) | ||

Probabilities(TInput, Int32, Double) | ||

Probabilities(TInput, Int32, Double) | ||

Probability(TInput) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
| |

Probability(TInput) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
| |

Probability(TInput, Int32) | ||

Probability(TInput, Double) | ||

Probability(TInput, Int32) | ||

Probability(TInput, Int32, Double) | ||

Scores(TInput) |
Computes numerical scores measuring the association between
each of the given sequence vectors and each
possible class.
(Inherited from IScoreTaggerTInput.) | |

Scores(TInput) |
Computes numerical scores measuring the association between
each of the given sequences vectors and each
possible class.
(Inherited from IScoreTaggerTInput.) | |

Scores(TInput, Double) |
Computes numerical scores measuring the association between
each of the given sequence vectors and each
possible class.
(Inherited from IScoreTaggerTInput.) | |

Scores(TInput, Int32) |
Computes numerical scores measuring the association between
each of the given sequence vectors and each
possible class.
(Inherited from IScoreTaggerTInput.) | |

Scores(TInput, Double) |
Computes numerical scores measuring the association between
each of the given sequences vectors and each
possible class.
(Inherited from IScoreTaggerTInput.) | |

Scores(TInput, Int32) |
Computes numerical scores measuring the association between
each of the given sequences vectors and each
possible class.
(Inherited from IScoreTaggerTInput.) | |

Scores(TInput, Int32, Double) | ||

Scores(TInput, Int32, Double) | ||

Transform(TInput) |
Applies the transformation to an input, producing an associated output.
(Inherited from ICovariantTransformTInput, TOutput.) | |

Transform(TInput) |
Applies the transformation to a set of input vectors,
producing an associated set of output vectors.
(Inherited from ICovariantTransformTInput, TOutput.) | |

Transform(TInput, TOutput) |
Applies the transformation to a set of input vectors,
producing an associated set of output vectors.
(Inherited from ITransformTInput, TOutput.) |

See Also