ILikelihoodTaggerTInput Interface |
Namespace: Accord.MachineLearning
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[]>
The ILikelihoodTaggerTInput type exposes the following members.
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.) |
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) |
Predicts a the log-likelihood that the sequence vector
has been generated by this log-likelihood tagger.
| |
LogLikelihood(TInput, Int32, Double) |
Predicts a the log-likelihood that the sequence vector
has been generated by this log-likelihood tagger.
| |
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) |
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) |
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, 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, 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.
| |
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) |
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) |
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) |
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) |
Predicts a the probabilities for each of the observations in
the sequence vector assuming each of the possible states in the
tagger model.
| |
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) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
| |
Probability(TInput, Double) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
| |
Probability(TInput, Int32) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
| |
Probability(TInput, Int32, Double) |
Predicts a the probability that the sequence vector
has been generated by this log-likelihood tagger.
| |
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) |
Computes numerical scores measuring the association between
each of the given sequence vectors and each
possible class.
(Inherited from IScoreTaggerTInput.) | |
Scores(TInput, Int32, Double) |
Computes numerical scores measuring the association between
each of the given sequences vectors and each
possible class.
(Inherited from IScoreTaggerTInput.) | |
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.) |