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HiddenMarkovModelTDistribution, TObservation Methods |
The HiddenMarkovModelTDistribution, TObservation generic type exposes the following members.
Methods| Name | Description | |
|---|---|---|
 | Clone |
Creates a new object that is a copy of the current instance.
|
| 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(TObservation, Int32) |
Computes class-label decisions for the given input.
(Overrides TaggerBaseTInputDecide(TInput, Int32).) |
| Decide(TObservation, Int32) |
Computes class-label decisions for the given input.
(Overrides TaggerBaseTInputDecide(TInput, Int32).) |
| Decode(TObservation) | Obsolete.
Calculates the most likely sequence of hidden states
that produced the given observation sequence.
|
| Decode(TObservation, Double) | Obsolete.
Calculates the most likely sequence of hidden states
that produced the given observation sequence.
|
| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) |
| Evaluate(TObservation) | Obsolete.
Calculates the likelihood that this model has generated the given sequence.
|
| Evaluate(TObservation, Int32) | Obsolete.
Calculates the log-likelihood that this model has generated the
given observation sequence along the given state path.
|
 | Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) |
| Generate(Int32) |
Generates a random vector of observations from the model.
|
| Generate(Int32, Int32, Double) |
Generates a random vector of observations from the model.
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| 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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| LogLikelihood(TInput) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
(Inherited from LikelihoodTaggerBaseTInput.) |
| LogLikelihood(TInput, Int32) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
(Inherited from LikelihoodTaggerBaseTInput.) |
| LogLikelihood(TInput, Int32) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
(Inherited from LikelihoodTaggerBaseTInput.) |
| LogLikelihood(TObservation, Int32) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger along
the given path of hidden states.
|
| LogLikelihood(TObservation, Double) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
(Overrides LikelihoodTaggerBaseTInputLogLikelihood(TInput, Double).) |
| LogLikelihood(TObservation, Int32) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger along
the given path of hidden states.
|
| LogLikelihood(TObservation, Int32, Double) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger along
the given path of hidden states.
|
| LogLikelihood(TObservation, Int32, Double) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
(Overrides LikelihoodTaggerBaseTInputLogLikelihood(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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| 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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| LogLikelihoods(TInput, Int32) |
Predicts a the log-likelihood for each of the observations in
the sequence vector assuming each of the possible states in the
tagger model.
(Inherited from LikelihoodTaggerBaseTInput.) |
| 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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| LogLikelihoods(TInput, Int32) |
Predicts a the log-likelihood for each of the observations in
the sequence vector assuming each of the possible states in the
tagger model.
(Inherited from LikelihoodTaggerBaseTInput.) |
| LogLikelihoods(TObservation, 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.
(Overrides LikelihoodTaggerBaseTInputLogLikelihoods(TInput, Double).) |
| LogLikelihoods(TInput, Int32, 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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| LogLikelihoods(TObservation, Int32, 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.
(Overrides LikelihoodTaggerBaseTInputLogLikelihoods(TInput, Int32, Double).) |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) |
| Posterior(TObservation) | Obsolete.
Calculates the probability of each hidden state for each
observation in the observation vector.
|
| Posterior(TObservation, Int32) | Obsolete.
Calculates the probability of each hidden state for each observation
in the observation vector, and uses those probabilities to decode the
most likely sequence of states for each observation in the sequence
using the posterior decoding method. See remarks for details.
|
 | Predict(TObservation) |
Predicts the next observation occurring after a given observation sequence.
|
| Predict(TObservation, Double) |
Predicts the next observation occurring after a given observation sequence.
|
| Predict(TObservation, Int32) |
Predicts the next observations occurring after a given observation sequence.
|
| Predict(TObservation, Int32, Double) |
Predicts the next observations occurring after a given observation sequence.
|
| PredictTMultivariate(TObservation, MultivariateMixtureTMultivariate) |
Predicts the next observation occurring after a given observation sequence.
|
| PredictTUnivariate(TObservation, MixtureTUnivariate) |
Predicts the next observation occurring after a given observation sequence.
|
| PredictTMultivariate(TObservation, Double, MultivariateMixtureTMultivariate) |
Predicts the next observation occurring after a given observation sequence.
|
| PredictTUnivariate(TObservation, Double, MixtureTUnivariate) |
Predicts the next observation occurring after a given observation sequence.
|
| 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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| Probabilities(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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| 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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| Probabilities(TInput, Int32) |
Predicts a the log-likelihood for each of the observations in
the sequence vector assuming each of the possible states in the
tagger model.
(Inherited from LikelihoodTaggerBaseTInput.) |
| Probabilities(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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| 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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| Probabilities(TInput, Int32, 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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| Probabilities(TInput, Int32, Double) |
Predicts a the probabilities for each of the observations in
the sequence vector assuming each of the possible states in the
tagger model.
(Inherited from LikelihoodTaggerBaseTInput.) |
| Probability(TInput) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
(Inherited from LikelihoodTaggerBaseTInput.) |
| Probability(TInput) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
(Inherited from LikelihoodTaggerBaseTInput.) |
| Probability(TInput, Int32) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
(Inherited from LikelihoodTaggerBaseTInput.) |
| Probability(TInput, Double) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
(Inherited from LikelihoodTaggerBaseTInput.) |
| Probability(TInput, Int32) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
(Inherited from LikelihoodTaggerBaseTInput.) |
| Probability(TInput, Int32, Double) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
(Inherited from LikelihoodTaggerBaseTInput.) |
| 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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| 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) |
Computes numerical scores measuring the association between
each of the given sequences vectors and each
possible class.
(Inherited from LikelihoodTaggerBaseTInput.) |
| Scores(TInput, Int32, Double) |
Computes numerical scores measuring the association between
each of the given sequence vectors and each
possible class.
(Inherited from ScoreTaggerBaseTInput.) |
| 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.
(Inherited from LikelihoodTaggerBaseTInput.) |
| 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