LikelihoodTaggerBase(TInput) Methods
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LikelihoodTaggerBaseTInput Methods

The LikelihoodTaggerBaseTInput generic type exposes the following members.

Methods
  NameDescription
Public methodDecide(TInput)
Computes class-label decisions for the given input.
(Inherited from TaggerBaseTInput.)
Public methodDecide(TInput)
Computes class-label decisions for the given input.
(Inherited from TaggerBaseTInput.)
Public methodDecide(TInput, Int32)
Computes class-label decisions for the given input.
(Inherited from TaggerBaseTInput.)
Public methodDecide(TInput, Int32)
Computes class-label decisions for the given input.
(Inherited from TaggerBaseTInput.)
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodLogLikelihood(TInput)
Predicts a the probability that the sequence vector has been generated by this log-likelihood tagger.
Public methodLogLikelihood(TInput)
Predicts a the probability that the sequence vector has been generated by this log-likelihood tagger.
Public methodLogLikelihood(TInput, Int32)
Predicts a the probability that the sequence vector has been generated by this log-likelihood tagger.
Public methodLogLikelihood(TInput, Double)
Predicts a the probability that the sequence vector has been generated by this log-likelihood tagger.
Public methodLogLikelihood(TInput, Int32)
Predicts a the probability that the sequence vector has been generated by this log-likelihood tagger.
Public methodLogLikelihood(TInput, Int32, Double)
Predicts a the probability that the sequence vector has been generated by this log-likelihood tagger.
Public methodLogLikelihoods(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.
Public methodLogLikelihoods(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.
Public methodLogLikelihoods(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.
Public methodLogLikelihoods(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.
Public methodLogLikelihoods(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.
Public methodLogLikelihoods(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.
Public methodLogLikelihoods(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.
Public methodLogLikelihoods(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.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodProbabilities(TInput)
Predicts a the probabilities for each of the observations in the sequence vector assuming each of the possible states in the tagger model.
Public methodProbabilities(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.
Public methodProbabilities(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.
Public methodProbabilities(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.
Public methodProbabilities(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.
Public methodProbabilities(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.
Public methodProbabilities(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.
Public methodProbabilities(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.
Public methodProbability(TInput)
Predicts a the probability that the sequence vector has been generated by this log-likelihood tagger.
Public methodProbability(TInput)
Predicts a the probability that the sequence vector has been generated by this log-likelihood tagger.
Public methodProbability(TInput, Int32)
Predicts a the probability that the sequence vector has been generated by this log-likelihood tagger.
Public methodProbability(TInput, Double)
Predicts a the probability that the sequence vector has been generated by this log-likelihood tagger.
Public methodProbability(TInput, Int32)
Predicts a the probability that the sequence vector has been generated by this log-likelihood tagger.
Public methodProbability(TInput, Int32, Double)
Predicts a the probability that the sequence vector has been generated by this log-likelihood tagger.
Public methodScores(TInput)
Computes numerical scores measuring the association between each of the given sequence vectors and each possible class.
(Inherited from ScoreTaggerBaseTInput.)
Public methodScores(TInput)
Computes numerical scores measuring the association between each of the given sequences vectors and each possible class.
(Inherited from ScoreTaggerBaseTInput.)
Public methodScores(TInput, Double)
Computes numerical scores measuring the association between each of the given sequences vectors and each possible class.
(Overrides ScoreTaggerBaseTInputScores(TInput, Double).)
Public methodScores(TInput, Double)
Computes numerical scores measuring the association between each of the given sequence vectors and each possible class.
(Inherited from ScoreTaggerBaseTInput.)
Public methodScores(TInput, Int32)
Computes numerical scores measuring the association between each of the given sequence vectors and each possible class.
(Inherited from ScoreTaggerBaseTInput.)
Public methodScores(TInput, Int32)
Computes numerical scores measuring the association between each of the given sequences vectors and each possible class.
(Inherited from ScoreTaggerBaseTInput.)
Public methodScores(TInput, Int32, Double)
Computes numerical scores measuring the association between each of the given sequences vectors and each possible class.
(Overrides ScoreTaggerBaseTInputScores(TInput, Int32, Double).)
Public methodScores(TInput, Int32, Double)
Computes numerical scores measuring the association between each of the given sequence vectors and each possible class.
(Inherited from ScoreTaggerBaseTInput.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
Public methodTransform(TInput)
Applies the transformation to an input, producing an associated output.
(Inherited from TaggerBaseTInput.)
Public methodTransform(TInput)
Applies the transformation to a set of input vectors, producing an associated set of output vectors.
(Inherited from TransformBaseTInput, TOutput.)
Public methodTransform(TInput, Double)
Applies the transformation to an input, producing an associated output.
Public methodTransform(TInput, TOutput)
Applies the transformation to an input, producing an associated output.
(Inherited from TransformBaseTInput, TOutput.)
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Extension Methods
  NameDescription
Public Extension MethodHasMethod
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)
Public Extension MethodIsEqual
Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.
(Defined by Matrix.)
Public Extension MethodTo(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.)
Public Extension MethodToTOverloaded.
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.)
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See Also