Accord.NET Framework

## LikelihoodTaggerBaseTInput Class |

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

Inheritance Hierarchy

SystemObject

Accord.MachineLearningTransformBaseTInput, Int32

Accord.MachineLearningTaggerBaseTInput

Accord.MachineLearningScoreTaggerBaseTInput

Accord.MachineLearningLikelihoodTaggerBaseTInput

Accord.Statistics.Models.MarkovHiddenMarkovModelTDistribution, TObservation

Accord.MachineLearningTransformBaseTInput, Int32

Accord.MachineLearningTaggerBaseTInput

Accord.MachineLearningScoreTaggerBaseTInput

Accord.MachineLearningLikelihoodTaggerBaseTInput

Accord.Statistics.Models.MarkovHiddenMarkovModelTDistribution, TObservation

Syntax

[SerializableAttribute] public abstract class LikelihoodTaggerBase<TInput> : ScoreTaggerBase<TInput>, 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 LikelihoodTaggerBaseTInput type exposes the following members.

Constructors

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

LikelihoodTaggerBaseTInput | Initializes a new instance of the LikelihoodTaggerBaseTInput class |

Properties

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

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

NumberOfInputs |
Gets the number of inputs accepted by the model.
(Inherited from TransformBaseTInput, TOutput.) | |

NumberOfOutputs |
Gets the number of outputs generated by the model.
(Inherited from TransformBaseTInput, TOutput.) |

Methods

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

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

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

Decide(TInput, Int32) |
Computes class-label decisions for the given input.
(Inherited from TaggerBaseTInput.) | |

Decide(TInput, Int32) |
Computes class-label decisions for the given input.
(Inherited from TaggerBaseTInput.) | |

Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) | |

Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) | |

GetHashCode | Serves as the default hash function. (Inherited from Object.) | |

GetType | Gets the Type of the current instance. (Inherited from Object.) | |

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

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

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

LogLikelihood(TInput, Double) | ||

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) | ||

MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) | |

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) | ||

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) |
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, Double) | ||

Probabilities(TInput, Int32, Double) | ||

Probability(TInput) | ||

Probability(TInput) | ||

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 ScoreTaggerBaseTInput.) | |

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

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

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

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

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

Scores(TInput, Int32, Double) | ||

Scores(TInput, Int32, Double) | ||

ToString | Returns a string that represents the current object. (Inherited from Object.) | |

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

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

Transform(TInput, Double) |
Applies the transformation to an input, producing an associated output.
| |

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

Extension Methods

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

HasMethod |
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.) | |

IsEqual |
Compares two objects for equality, performing an elementwise
comparison if the elements are vectors or matrices.
(Defined by Matrix.) | |

To(Type) | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) | |

ToT | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) |

See Also