MultilabelLikelihoodClassifierBaseTInput Class

Base class for generative multi-label classifiers.

Inheritance Hierarchy

SystemObject
  Accord.MachineLearningTransformBaseTInput, Boolean
    Accord.MachineLearningClassifierBaseTInput, Boolean
      Accord.MachineLearningMultilabelClassifierBaseTInput
        Accord.MachineLearningMultilabelScoreClassifierBaseTInput
          Accord.MachineLearningMultilabelLikelihoodClassifierBaseTInput
            Accord.MachineLearningOneVsRestTModel, TInput

Namespace: Accord.MachineLearning
Assembly: Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0

Syntax

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[SerializableAttribute]
public abstract class MultilabelLikelihoodClassifierBase<TInput> : MultilabelScoreClassifierBase<TInput>, 
	IMultilabelLikelihoodClassifier<TInput>, IMultilabelLikelihoodClassifier<TInput, int>, IMultilabelOutLikelihoodClassifier<TInput, int>, 
	IMultilabelLikelihoodClassifierBase<TInput, int>, IMultilabelScoreClassifierBase<TInput, int>, IMultilabelOutScoreClassifier<TInput, int>, 
	IMultilabelRefLikelihoodClassifier<TInput, int[]>, IMultilabelLikelihoodClassifierBase<TInput, int[]>, 
	IMultilabelScoreClassifierBase<TInput, int[]>, IMultilabelRefScoreClassifier<TInput, int[]>, 
	IMultilabelLikelihoodClassifier<TInput, double>, IMultilabelOutLikelihoodClassifier<TInput, double>, 
	IMultilabelLikelihoodClassifierBase<TInput, double>, IMultilabelScoreClassifierBase<TInput, double>, 
	IMultilabelOutScoreClassifier<TInput, double>, IMultilabelRefLikelihoodClassifier<TInput, double[]>, 
	IMultilabelLikelihoodClassifierBase<TInput, double[]>, IMultilabelScoreClassifierBase<TInput, double[]>, 
	IMultilabelRefScoreClassifier<TInput, double[]>, IMultilabelRefLikelihoodClassifier<TInput, bool[]>, 
	IMultilabelLikelihoodClassifierBase<TInput, bool[]>, IMultilabelScoreClassifierBase<TInput, bool[]>, 
	IMultilabelRefScoreClassifier<TInput, bool[]>, IMultilabelScoreClassifier<TInput>, IMultilabelScoreClassifier<TInput, int>, 
	IClassifier<TInput, int>, IClassifier, ITransform<TInput, int>, 
	ICovariantTransform<TInput, int>, ITransform, IMultilabelScoreClassifier<TInput, double>, 
	IClassifier<TInput, double>, ITransform<TInput, double>, 
	ICovariantTransform<TInput, double>, IMultilabelClassifier<TInput>, IMultilabelClassifier<TInput, int[]>, 
	IClassifier<TInput, int[]>, ITransform<TInput, int[]>, 
	ICovariantTransform<TInput, int[]>, IMultilabelClassifier<TInput, bool[]>, 
	IClassifier<TInput, bool[]>, ITransform<TInput, bool[]>, 
	ICovariantTransform<TInput, bool[]>, IMultilabelClassifier<TInput, double[]>, 
	IClassifier<TInput, double[]>, ITransform<TInput, double[]>, 
	ICovariantTransform<TInput, double[]>, IMulticlassLikelihoodClassifier<TInput>, IMulticlassLikelihoodClassifier<TInput, int>, 
	IMulticlassOutLikelihoodClassifier<TInput, int>, IMulticlassOutScoreClassifier<TInput, int>, IMulticlassScoreClassifierBase<TInput, int>, 
	IMulticlassLikelihoodClassifierBase<TInput, int>, IMulticlassRefLikelihoodClassifier<TInput, int[]>, IMulticlassRefScoreClassifier<TInput, int[]>, 
	IMulticlassScoreClassifier<TInput, int>, IMulticlassLikelihoodClassifier<TInput, double>, 
	IMulticlassOutLikelihoodClassifier<TInput, double>, IMulticlassOutScoreClassifier<TInput, double>, 
	IMulticlassScoreClassifierBase<TInput, double>, IMulticlassLikelihoodClassifierBase<TInput, double>, 
	IMulticlassRefLikelihoodClassifier<TInput, double[]>, IMulticlassRefScoreClassifier<TInput, double[]>, 
	IMulticlassScoreClassifier<TInput, double>, IMulticlassRefLikelihoodClassifier<TInput, bool[]>, 
	IMulticlassRefScoreClassifier<TInput, bool[]>, IMulticlassScoreClassifier<TInput>, IMulticlassClassifier<TInput>, 
	IMulticlassClassifier<TInput, int>, IMulticlassClassifier<TInput, double>

<SerializableAttribute>
Public MustInherit Class MultilabelLikelihoodClassifierBase(Of TInput)
	Inherits MultilabelScoreClassifierBase(Of TInput)
	Implements IMultilabelLikelihoodClassifier(Of TInput), IMultilabelLikelihoodClassifier(Of TInput, Integer), 
	IMultilabelOutLikelihoodClassifier(Of TInput, Integer), IMultilabelLikelihoodClassifierBase(Of TInput, Integer), 
	IMultilabelScoreClassifierBase(Of TInput, Integer), IMultilabelOutScoreClassifier(Of TInput, Integer), 
	IMultilabelRefLikelihoodClassifier(Of TInput, Integer()), IMultilabelLikelihoodClassifierBase(Of TInput, Integer()), 
	IMultilabelScoreClassifierBase(Of TInput, Integer()), IMultilabelRefScoreClassifier(Of TInput, Integer()), 
	IMultilabelLikelihoodClassifier(Of TInput, Double), IMultilabelOutLikelihoodClassifier(Of TInput, Double), 
	IMultilabelLikelihoodClassifierBase(Of TInput, Double), IMultilabelScoreClassifierBase(Of TInput, Double), 
	IMultilabelOutScoreClassifier(Of TInput, Double), IMultilabelRefLikelihoodClassifier(Of TInput, Double()), 
	IMultilabelLikelihoodClassifierBase(Of TInput, Double()), IMultilabelScoreClassifierBase(Of TInput, Double()), 
	IMultilabelRefScoreClassifier(Of TInput, Double()), IMultilabelRefLikelihoodClassifier(Of TInput, Boolean()), 
	IMultilabelLikelihoodClassifierBase(Of TInput, Boolean()), IMultilabelScoreClassifierBase(Of TInput, Boolean()), 
	IMultilabelRefScoreClassifier(Of TInput, Boolean()), IMultilabelScoreClassifier(Of TInput), 
	IMultilabelScoreClassifier(Of TInput, Integer), IClassifier(Of TInput, Integer), 
	IClassifier, ITransform(Of TInput, Integer), ICovariantTransform(Of TInput, Integer), 
	ITransform, IMultilabelScoreClassifier(Of TInput, Double), IClassifier(Of TInput, Double), 
	ITransform(Of TInput, Double), ICovariantTransform(Of TInput, Double), 
	IMultilabelClassifier(Of TInput), IMultilabelClassifier(Of TInput, Integer()), 
	IClassifier(Of TInput, Integer()), ITransform(Of TInput, Integer()), 
	ICovariantTransform(Of TInput, Integer()), IMultilabelClassifier(Of TInput, Boolean()), 
	IClassifier(Of TInput, Boolean()), ITransform(Of TInput, Boolean()), 
	ICovariantTransform(Of TInput, Boolean()), IMultilabelClassifier(Of TInput, Double()), 
	IClassifier(Of TInput, Double()), ITransform(Of TInput, Double()), 
	ICovariantTransform(Of TInput, Double()), IMulticlassLikelihoodClassifier(Of TInput), 
	IMulticlassLikelihoodClassifier(Of TInput, Integer), IMulticlassOutLikelihoodClassifier(Of TInput, Integer), 
	IMulticlassOutScoreClassifier(Of TInput, Integer), IMulticlassScoreClassifierBase(Of TInput, Integer), 
	IMulticlassLikelihoodClassifierBase(Of TInput, Integer), IMulticlassRefLikelihoodClassifier(Of TInput, Integer()), 
	IMulticlassRefScoreClassifier(Of TInput, Integer()), IMulticlassScoreClassifier(Of TInput, Integer), 
	IMulticlassLikelihoodClassifier(Of TInput, Double), IMulticlassOutLikelihoodClassifier(Of TInput, Double), 
	IMulticlassOutScoreClassifier(Of TInput, Double), IMulticlassScoreClassifierBase(Of TInput, Double), 
	IMulticlassLikelihoodClassifierBase(Of TInput, Double), IMulticlassRefLikelihoodClassifier(Of TInput, Double()), 
	IMulticlassRefScoreClassifier(Of TInput, Double()), IMulticlassScoreClassifier(Of TInput, Double), 
	IMulticlassRefLikelihoodClassifier(Of TInput, Boolean()), IMulticlassRefScoreClassifier(Of TInput, Boolean()), 
	IMulticlassScoreClassifier(Of TInput), IMulticlassClassifier(Of TInput), IMulticlassClassifier(Of TInput, Integer), 
	IMulticlassClassifier(Of TInput, Double)

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Type Parameters

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

The MultilabelLikelihoodClassifierBaseTInput type exposes the following members.

Constructors

	Name	Description
	MultilabelLikelihoodClassifierBaseTInput	Initializes a new instance of the MultilabelLikelihoodClassifierBaseTInput class

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Properties

	Name	Description
	NumberOfClasses	Gets the number of classes expected and recognized by the classifier. (Inherited from ClassifierBaseTInput, TClasses.)
	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.)

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Methods

	Name	Description
	Decide(TInput)	Computes class-label decisions for a given set of input vectors. (Inherited from ClassifierBaseTInput, TClasses.)
	Decide(TInput)	Computes a class-label decision for a given input. (Inherited from MultilabelClassifierBaseTInput.)
	Decide(TInput, TClasses)	Computes a class-label decision for a given input. (Inherited from ClassifierBaseTInput, TClasses.)
	Decide(TInput, Boolean)	Computes class-label decisions for the given input. (Inherited from MultilabelClassifierBaseTInput.)
	Decide(TInput, Double)	Computes class-label decisions for the given input. (Inherited from MultilabelClassifierBaseTInput.)
	Decide(TInput, Int32)	Computes whether a class label applies to an input vector. (Inherited from MultilabelClassifierBaseTInput.)
	Decide(TInput, Int32)	Computes class-label decisions for the given input. (Inherited from MultilabelClassifierBaseTInput.)
	Decide(TInput, Double)	Computes a class-label decision for a given input. (Inherited from MultilabelClassifierBaseTInput.)
	Decide(TInput, Int32)	Computes a class-label decision for a given input. (Inherited from MultilabelClassifierBaseTInput.)
	Decide(TInput, Double)	Computes a class-label decision for a given input. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Decide(TInput, Int32)	Computes a class-label decision for a given input. (Inherited from MultilabelScoreClassifierBaseTInput.)
	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, Int32)	Computes the log-likelihood that the given input vector belongs to the specified classIndex.
	LogLikelihood(TInput, Int32)	Computes the log-likelihood that the given input vector belongs to the specified classIndex.
	LogLikelihood(TInput, Int32)	Computes the log-likelihood that the given input vector belongs to the specified classIndex.
	LogLikelihood(TInput, Int32, Boolean)	Computes a log-likelihood measuring the association between the given input vector and a given classIndex.
	LogLikelihood(TInput, Int32, Double)	Computes the log-likelihood that the given input vector belongs to the specified classIndex.
	LogLikelihood(TInput, Int32, Double)	Computes the log-likelihood that the given input vector belongs to the specified classIndex.
	LogLikelihoods(TInput)	Computes the log-likelihood that the given input vector belongs to each of the possible classes.
	LogLikelihoods(TInput)	Computes the log-likelihood that the given input vector belongs to each of the possible classes.
	LogLikelihoods(TInput, Boolean)	Predicts a class label vector for the given input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Double)	Predicts a class label vector for the given input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Double)	Computes the log-likelihood that the given input vector belongs to each of the possible classes.
	LogLikelihoods(TInput, Double)	Predicts a class label vector for the given input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Int32)	Predicts a class label vector for the given input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Int32)	Predicts a class label vector for the given input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Boolean)	Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Double)	Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Double)	Computes the log-likelihood that the given input vector belongs to each of the possible classes.
	LogLikelihoods(TInput, Double)	Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Int32)	Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Int32)	Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Boolean, Double)	Predicts a class label vector for the given input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Double, Double)	Predicts a class label vector for the given input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Double, Double)	Predicts a class label vector for the given input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Int32, Double)	Predicts a class label vector for the given input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Int32, Double)	Predicts a class label vector for the given input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Boolean, Double)	Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Double, Double)	Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Double, Double)	Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Int32, Double)	Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	LogLikelihoods(TInput, Int32, Double)	Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	Probabilities(TInput)	Computes the probabilities that the given input vector belongs to each of the possible classes.
	Probabilities(TInput)	Computes the probabilities that the given input vector belongs to each of the possible classes.
	Probabilities(TInput, Boolean)	Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Double)	Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Double)	Computes the probabilities that the given input vector belongs to each of the possible classes.
	Probabilities(TInput, Double)	Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Int32)	Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Int32)	Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Boolean)	Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Double)	Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Double)	Computes the probabilities that the given input vector belongs to each of the possible classes.
	Probabilities(TInput, Double)	Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Int32)	Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Int32)	Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Boolean, Double)	Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Double, Double)	Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Double, Double)	Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Int32, Double)	Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Int32, Double)	Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Boolean, Double)	Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Double, Double)	Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Double, Double)	Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Int32, Double)	Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
	Probabilities(TInput, Int32, Double)	Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
	Probability(TInput, Int32)	Computes the probability that the given input vector belongs to the specified classIndex.
	Probability(TInput, Int32)	Computes the probability that the given input vector belongs to the specified classIndex.
	Probability(TInput, Int32)	Computes the probability that the given input vector belongs to the specified classIndex.
	Probability(TInput, Int32, Double)	Computes the probability that the given input vector belongs to the specified classIndex.
	Probability(TInput, Int32, Double)	Computes the probability that the given input vector belongs to the specified classIndex.
	Score(TInput, Int32)	Computes a numerical score measuring the association between the given input vector and a given classIndex. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Score(TInput, Int32)	Computes a numerical score measuring the association between the given input vector and a given classIndex. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Score(TInput, Int32)	Computes a numerical score measuring the association between the given input vector and a given classIndex. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Score(TInput, Int32, Boolean)	Computes a numerical score measuring the association between the given input vector and a given classIndex. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Score(TInput, Int32, Double)	Computes a numerical score measuring the association between the given input vector and a given classIndex. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Score(TInput, Int32, Double)	Computes a numerical score measuring the association between the given input vector and a given classIndex. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Scores(TInput)	Computes a numerical score measuring the association between the given input vector and each class. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Scores(TInput)	Computes a numerical score measuring the association between the given input vector and each class. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Scores(TInput, Boolean)	Predicts a class label vector for the given input vector, returning a numerical score measuring the strength of association of the input vector to each of the possible classes. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Scores(TInput, Double)	Computes a numerical score measuring the association between the given input vector and each class. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Scores(TInput, Double)	Computes a numerical score measuring the association between the given input vector and each class. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Scores(TInput, Int32)	Predicts a class label vector for each input vector, returning a numerical score measuring the strength of association of the input vector to each of the possible classes. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Scores(TInput, Boolean, Double)	Predicts a class label vector for the given input vector, returning a numerical score measuring the strength of association of the input vector to each of the possible classes. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Scores(TInput, Boolean, Double)	Predicts a class label vector for each input vector, returning a numerical score measuring the strength of association of the input vector to each of the possible classes. (Inherited from MultilabelScoreClassifierBaseTInput.)
	ToMulticlass	Views this instance as a multi-class generative classifier.
	ToMulticlassT	Views this instance as a multi-class generative classifier.
	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 ClassifierBaseTInput, TClasses.)
	Transform(TInput)	Applies the transformation to a set of input vectors, producing an associated set of output vectors. (Inherited from TransformBaseTInput, TOutput.)
	Transform(TInput, Boolean)	Applies the transformation to an input, producing an associated output. (Inherited from MultilabelClassifierBaseTInput.)
	Transform(TInput, Int32)	Applies the transformation to an input, producing an associated output. (Inherited from MultilabelClassifierBaseTInput.)
	Transform(TInput, Boolean)	Applies the transformation to an input, producing an associated output. (Inherited from MultilabelClassifierBaseTInput.)
	Transform(TInput, Int32)	Applies the transformation to an input, producing an associated output. (Inherited from MultilabelClassifierBaseTInput.)
	Transform(TInput, Double)	Applies the transformation to an input, producing an associated output. (Overrides MultilabelScoreClassifierBaseTInputTransform(TInput, Double).)
	Transform(TInput, Double)	Applies the transformation to an input, producing an associated output. (Overrides MultilabelScoreClassifierBaseTInputTransform(TInput, Double).)
	Transform(TInput, Double)	Applies the transformation to an input, producing an associated output. (Inherited from MultilabelScoreClassifierBaseTInput.)
	Transform(TInput, Int32)	Applies the transformation to an input, producing an associated output. (Inherited from MultilabelScoreClassifierBaseTInput.)

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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.)

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Reference

Accord.MachineLearning Namespace

MultilabelLikelihoodClassifierBaseAddLanguageSpecificTextSet("LSTDA2052A4_0?cs=&lt;|vb=(Of |cpp=&lt;|fs=&lt;'|nu=(");TInputAddLanguageSpecificTextSet("LSTDA2052A4_1?cs=&gt;|vb=)|cpp=&gt;|fs=&gt;|nu=)"); Class

Type Parameters

Reference

MultilabelLikelihoodClassifierBaseTInput Class