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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.

Namespace:  Accord.MachineLearning
Assembly:  Accord (in Accord.dll) Version: 3.8.0
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[]>
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Type Parameters

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

The ILikelihoodTaggerTInput type exposes the following members.

Properties
  NameDescription
Public propertyNumberOfClasses
Gets or sets the number of classes expected and recognized by the classifier.
(Inherited from IClassifier.)
Public propertyNumberOfInputs
Gets or sets the number of inputs accepted by the model.
(Inherited from ITransform.)
Public propertyNumberOfOutputs
Gets or sets the number of outputs generated by the model.
(Inherited from ITransform.)
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Methods
  NameDescription
Public methodDecide(TInput)
Computes a class-label decision for a given input.
(Inherited from IClassifierTInput, TClasses.)
Public methodDecide(TInput)
Computes class-label decisions for each vector in the given input.
(Inherited from IClassifierTInput, TClasses.)
Public methodDecide(TInput, TClasses)
Computes class-label decisions for each vector in the given input.
(Inherited from IClassifierTInput, TClasses.)
Public methodDecide(TInput, TClasses)
Computes class-label decisions for the given input.
(Inherited from IMultilabelClassifierTInput, TClasses.)
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 log-likelihood that the sequence vector has been generated by this log-likelihood tagger.
Public methodLogLikelihood(TInput, Int32)
Predicts a the log-likelihood that the sequence vector has been generated by this log-likelihood tagger.
Public methodLogLikelihood(TInput, Double)
Predicts a the log-likelihood that the sequence vector has been generated by this log-likelihood tagger.
Public methodLogLikelihood(TInput, Int32)
Predicts a the log-likelihood that the sequence vector has been generated by this log-likelihood tagger.
Public methodLogLikelihood(TInput, Int32, Double)
Predicts a the log-likelihood 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.
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 probabilities 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 probabilities 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 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 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 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 IScoreTaggerTInput.)
Public methodScores(TInput)
Computes numerical scores measuring the association between each of the given sequences vectors and each possible class.
(Inherited from IScoreTaggerTInput.)
Public methodScores(TInput, Double)
Computes numerical scores measuring the association between each of the given sequence vectors and each possible class.
(Inherited from IScoreTaggerTInput.)
Public methodScores(TInput, Int32)
Computes numerical scores measuring the association between each of the given sequence vectors and each possible class.
(Inherited from IScoreTaggerTInput.)
Public methodScores(TInput, Double)
Computes numerical scores measuring the association between each of the given sequences vectors and each possible class.
(Inherited from IScoreTaggerTInput.)
Public methodScores(TInput, Int32)
Computes numerical scores measuring the association between each of the given sequences vectors and each possible class.
(Inherited from IScoreTaggerTInput.)
Public methodScores(TInput, Int32, Double)
Computes numerical scores measuring the association between each of the given sequence vectors and each possible class.
(Inherited from IScoreTaggerTInput.)
Public methodScores(TInput, Int32, Double)
Computes numerical scores measuring the association between each of the given sequences vectors and each possible class.
(Inherited from IScoreTaggerTInput.)
Public methodTransform(TInput)
Applies the transformation to an input, producing an associated output.
(Inherited from ICovariantTransformTInput, TOutput.)
Public methodTransform(TInput)
Applies the transformation to a set of input vectors, producing an associated set of output vectors.
(Inherited from ICovariantTransformTInput, TOutput.)
Public methodTransform(TInput, TOutput)
Applies the transformation to a set of input vectors, producing an associated set of output vectors.
(Inherited from ITransformTInput, TOutput.)
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See Also