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MulticlassLikelihoodClassifierBaseTInput Class

Base class for generative multi-class classifiers.
Inheritance Hierarchy
SystemObject
  Accord.MachineLearningTransformBaseTInput, Int32
    Accord.MachineLearningClassifierBaseTInput, Int32
      Accord.MachineLearningMulticlassClassifierBaseTInput
        Accord.MachineLearningMulticlassScoreClassifierBaseTInput
          Accord.MachineLearningMulticlassLikelihoodClassifierBaseTInput
            Accord.MachineLearning.BayesBayesTDistribution, TInput
            Accord.MachineLearningOneVsOneTBinary, TInput
            Accord.Statistics.Models.MarkovBaseHiddenMarkovClassifierTModel, TDistribution, TObservation
            Accord.Statistics.Models.RegressionMultinomialLogisticRegression

Namespace:  Accord.MachineLearning
Assembly:  Accord.Statistics (in Accord.Statistics.dll) Version: 3.5.0
Syntax
[SerializableAttribute]
public abstract class MulticlassLikelihoodClassifierBase<TInput> : MulticlassScoreClassifierBase<TInput>, 
	IMulticlassLikelihoodClassifier<TInput>, IMulticlassOutLikelihoodClassifier<TInput, int>, IMulticlassOutScoreClassifier<TInput, int>, 
	IMulticlassScoreClassifier<TInput, int>, IClassifier<TInput, int>, ITransform<TInput, int>, 
	ITransform, IMultilabelOutScoreClassifier<TInput, int>, IMultilabelScoreClassifier<TInput, int>, 
	IMultilabelOutLikelihoodClassifier<TInput, int>, IMultilabelLikelihoodClassifier<TInput, int>, IMulticlassLikelihoodClassifier<TInput, int>, 
	IMulticlassOutLikelihoodClassifier<TInput, double>, IMulticlassOutScoreClassifier<TInput, double>, 
	IMulticlassScoreClassifier<TInput, double>, IClassifier<TInput, double>, 
	ITransform<TInput, double>, IMultilabelOutScoreClassifier<TInput, double>, 
	IMultilabelScoreClassifier<TInput, double>, IMultilabelOutLikelihoodClassifier<TInput, double>, 
	IMultilabelLikelihoodClassifier<TInput, double>, IMulticlassLikelihoodClassifier<TInput, double>, 
	IMulticlassRefLikelihoodClassifier<TInput, int[]>, IMulticlassRefScoreClassifier<TInput, int[]>, 
	IMultilabelRefScoreClassifier<TInput, int[]>, IMultilabelScoreClassifier<TInput, int[]>, 
	IClassifier<TInput, int[]>, ITransform<TInput, int[]>, 
	IMultilabelRefLikelihoodClassifier<TInput, int[]>, IMultilabelLikelihoodClassifier<TInput, int[]>, 
	IMulticlassRefLikelihoodClassifier<TInput, bool[]>, IMulticlassRefScoreClassifier<TInput, bool[]>, 
	IMultilabelRefScoreClassifier<TInput, bool[]>, IMultilabelScoreClassifier<TInput, bool[]>, 
	IClassifier<TInput, bool[]>, ITransform<TInput, bool[]>, 
	IMultilabelRefLikelihoodClassifier<TInput, bool[]>, IMultilabelLikelihoodClassifier<TInput, bool[]>, 
	IMulticlassRefLikelihoodClassifier<TInput, double[]>, IMulticlassRefScoreClassifier<TInput, double[]>, 
	IMultilabelRefScoreClassifier<TInput, double[]>, IMultilabelScoreClassifier<TInput, double[]>, 
	IClassifier<TInput, double[]>, ITransform<TInput, double[]>, 
	IMultilabelRefLikelihoodClassifier<TInput, double[]>, IMultilabelLikelihoodClassifier<TInput, double[]>, 
	IMulticlassScoreClassifier<TInput>, IMultilabelScoreClassifier<TInput>, IMultilabelClassifier<TInput>, 
	IMultilabelClassifier<TInput, int[]>, IMultilabelClassifier<TInput, bool[]>, 
	IMultilabelClassifier<TInput, double[]>, IMulticlassClassifier<TInput>, IMulticlassClassifier<TInput, int>, 
	IMulticlassClassifier<TInput, double>, IMultilabelLikelihoodClassifier<TInput>
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Type Parameters

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

The MulticlassLikelihoodClassifierBaseTInput type exposes the following members.

Constructors
  NameDescription
Protected methodMulticlassLikelihoodClassifierBaseTInput
Initializes a new instance of the MulticlassLikelihoodClassifierBaseTInput class
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Properties
Methods
  NameDescription
Public methodDecide(TInput)
Computes class-label decisions for a given set of input vectors.
(Inherited from ClassifierBaseTInput, TClasses.)
Public methodDecide(TInput)
Computes a class-label decision for a given input.
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodDecide(TInput, TClasses)
Computes a class-label decision for a given input.
(Inherited from ClassifierBaseTInput, TClasses.)
Public methodDecide(TInput, Boolean)
Computes class-label decisions for the given input.
(Inherited from MulticlassClassifierBaseTInput.)
Public methodDecide(TInput, Double)
Computes class-label decisions for the given input.
(Inherited from MulticlassClassifierBaseTInput.)
Public methodDecide(TInput, Int32)
Computes class-label decisions for the given input.
(Inherited from MulticlassClassifierBaseTInput.)
Public methodDecide(TInput, Double)
Computes a class-label decision for a given input.
(Inherited from MulticlassClassifierBaseTInput.)
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)
Computes the log-likelihood that the given input vector belongs to its most plausible class.
Public methodLogLikelihood(TInput)
Computes the log-likelihood that the given input vectors belongs to each of the possible classes.
Public methodLogLikelihood(TInput, Double)
Predicts a class label vector for the given input vector, returning the log-likelihood that the input vector belongs to its predicted class.
Public methodLogLikelihood(TInput, Int32)
Computes the log-likelihood that the given input vector belongs to the specified classIndex.
Public methodLogLikelihood(TInput, Int32)
Predicts a class label vector for the given input vector, returning the log-likelihood that the input vector belongs to its predicted class.
Public methodLogLikelihood(TInput, Double)
Computes the log-likelihood that the given input vectors belongs to each of the possible classes.
Public methodLogLikelihood(TInput, Double)
Predicts a class label for each input vector, returning the log-likelihood that each vector belongs to its predicted class.
Public methodLogLikelihood(TInput, Int32)
Computes the log-likelihood that the given input vector belongs to the specified classIndex.
Public methodLogLikelihood(TInput, Int32)
Computes the log-likelihood that the given input vector belongs to the specified classIndex.
Public methodLogLikelihood(TInput, Int32)
Predicts a class label for each input vector, returning the log-likelihood that each vector belongs to its predicted class.
Public methodLogLikelihood(TInput, Double, Double)
Predicts a class label for each input vector, returning the log-likelihood that each vector belongs to its predicted class.
Public methodLogLikelihood(TInput, Int32, Double)
Computes the log-likelihood that the given input vector belongs to the specified classIndex.
Public methodLogLikelihood(TInput, Int32, Double)
Computes the log-likelihood that the given input vector belongs to the specified classIndex.
Public methodLogLikelihood(TInput, Int32, Double)
Predicts a class label for each input vector, returning the log-likelihood that each vector belongs to its predicted class.
Public methodLogLikelihoods(TInput)
Computes the log-likelihood that the given input vector belongs to each of the possible classes.
Public methodLogLikelihoods(TInput)
Computes the log-likelihood that the given input vectors belongs to each of the possible classes.
Public methodLogLikelihoods(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.
Public methodLogLikelihoods(TInput, Double)
Computes the log-likelihood that the given input vector belongs to each of the possible classes.
Public methodLogLikelihoods(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.
Public methodLogLikelihoods(TInput, Double)
Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
Public methodLogLikelihoods(TInput, Double)
Computes the log-likelihood that the given input vector belongs to each of the possible classes.
Public methodLogLikelihoods(TInput, Int32)
Computes the log-likelihood that the given input vector belongs to the specified classIndex.
Public methodLogLikelihoods(TInput, Int32)
Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
Public methodLogLikelihoods(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.
Public methodLogLikelihoods(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.
Public methodLogLikelihoods(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.
Public methodLogLikelihoods(TInput, Int32, Double)
Computes the log-likelihood that the given input vector belongs to the specified classIndex.
Public methodLogLikelihoods(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.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodProbabilities(TInput)
Computes the probabilities that the given input vector belongs to each of the possible classes.
Public methodProbabilities(TInput)
Computes the probabilities that the given input vector belongs to each of the possible classes.
Public methodProbabilities(TInput, Double)
Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
Public methodProbabilities(TInput, Double)
Computes the probabilities that the given input vector belongs to each of the possible classes.
Public methodProbabilities(TInput, Int32)
Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
Public methodProbabilities(TInput, Double)
Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
Public methodProbabilities(TInput, Double)
Computes the probabilities that the given input vector belongs to each of the possible classes.
Public methodProbabilities(TInput, Int32)
Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
Public methodProbabilities(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.
Public methodProbabilities(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.
Public methodProbabilities(TInput, Double, Double)
Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
Public methodProbabilities(TInput, Int32, Double)
Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
Public methodProbability(TInput)
Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
Public methodProbability(TInput)
Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
Public methodProbability(TInput, Double)
Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
Public methodProbability(TInput, Int32)
Computes the probability that the given input vector belongs to the specified classIndex.
Public methodProbability(TInput, Int32)
Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
Public methodProbability(TInput, Double)
Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
Public methodProbability(TInput, Double)
Predicts a class label for each input vector, returning the probability that each vector belongs to its predicted class.
Public methodProbability(TInput, Int32)
Computes the probability that the given input vector belongs to the specified classIndex.
Public methodProbability(TInput, Int32)
Computes the probability that the given input vector belongs to the specified classIndex.
Public methodProbability(TInput, Int32)
Predicts a class label for each input vector, returning the probability that each vector belongs to its predicted class.
Public methodProbability(TInput, Double, Double)
Predicts a class label for each input vector, returning the probability that each vector belongs to its predicted class.
Public methodProbability(TInput, Int32, Double)
Computes the probability that the given input vector belongs to the specified classIndex.
Public methodProbability(TInput, Int32, Double)
Computes the probability that the given input vector belongs to the specified classIndex.
Public methodProbability(TInput, Int32, Double)
Predicts a class label for each input vector, returning the probability that each vector belongs to its predicted class.
Public methodScore(TInput)
Computes a numerical score measuring the association between the given input vector and its most strongly associated class (as predicted by the classifier).
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScore(TInput)
Computes a numerical score measuring the association between the given input vector and its most strongly associated class (as predicted by the classifier).
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScore(TInput, Int32)
Computes a numerical score measuring the association between the given input vector and a given classIndex.
(Overrides MulticlassScoreClassifierBaseTInputScore(TInput, Int32).)
Public methodScore(TInput, Int32)
Predicts a class label for the input vector, returning a numerical score measuring the strength of association of the input vector to its most strongly related class.
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScore(TInput, Double)
Computes a numerical score measuring the association between the given input vector and its most strongly associated class (as predicted by the classifier).
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScore(TInput, Int32)
Computes a numerical score measuring the association between the given input vector and a given classIndex.
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScore(TInput, Int32)
Computes a numerical score measuring the association between the given input vector and a given classIndex.
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScore(TInput, Int32)
Predicts a class label for each input vector, returning a numerical score measuring the strength of association of the input vector to the most strongly related class.
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScore(TInput, Int32, Double)
Computes a numerical score measuring the association between the given input vector and a given classIndex.
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScore(TInput, Int32, Double)
Computes a numerical score measuring the association between the given input vector and a given classIndex.
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScore(TInput, Int32, Double)
Predicts a class label for each input vector, returning a numerical score measuring the strength of association of the input vector to the most strongly related class.
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScores(TInput)
Computes a numerical score measuring the association between the given input vector and each class.
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScores(TInput)
Computes a numerical score measuring the association between the given input vector and each class.
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScores(TInput, Double)
Computes a numerical score measuring the association between the given input vector and each class.
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScores(TInput, Int32)
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 MulticlassScoreClassifierBaseTInput.)
Public methodScores(TInput, Double)
Computes a numerical score measuring the association between the given input vector and each class.
(Inherited from MulticlassScoreClassifierBaseTInput.)
Public methodScores(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 MulticlassScoreClassifierBaseTInput.)
Public methodScores(TInput, Int32, 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 MulticlassScoreClassifierBaseTInput.)
Public methodScores(TInput, Int32, 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 MulticlassScoreClassifierBaseTInput.)
Public methodToMulticlass
Views this instance as a multi-class generative classifier.
Public methodToMultilabel
Views this instance as a multi-label generative classifier, giving access to more advanced methods, such as the prediction of one-hot vectors.
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 ClassifierBaseTInput, TClasses.)
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, TClasses)
Applies the transformation to an input, producing an associated output.
(Inherited from ClassifierBaseTInput, TClasses.)
Public methodTransform(TInput, Boolean)
Applies the transformation to an input, producing an associated output.
(Inherited from MulticlassClassifierBaseTInput.)
Public methodTransform(TInput, Int32)
Applies the transformation to an input, producing an associated output.
(Inherited from MulticlassClassifierBaseTInput.)
Public methodTransform(TInput, Boolean)
Applies the transformation to an input, producing an associated output.
(Inherited from MulticlassClassifierBaseTInput.)
Public methodTransform(TInput, Double)
Applies the transformation to an input, producing an associated output.
(Inherited from MulticlassClassifierBaseTInput.)
Public methodTransform(TInput, Int32)
Applies the transformation to an input, producing an associated output.
(Inherited from MulticlassClassifierBaseTInput.)
Public methodTransform(TInput, Double)
Applies the transformation to an input, producing an associated output.
(Overrides MulticlassScoreClassifierBaseTInputTransform(TInput, Double).)
Public methodTransform(TInput, Double)
Applies the transformation to an input, producing an associated output.
(Overrides MulticlassScoreClassifierBaseTInputTransform(TInput, Double).)
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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 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.)
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 Matrix.)
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See Also