BinaryLikelihoodClassifierBaseTInput Class

Base class for generative binary classifiers.

Inheritance Hierarchy

SystemObject
  Accord.MachineLearningTransformBaseTInput, Boolean
    Accord.MachineLearningClassifierBaseTInput, Boolean
      Accord.MachineLearningBinaryClassifierBaseTInput
        Accord.MachineLearningBinaryScoreClassifierBaseTInput
          Accord.MachineLearningBinaryLikelihoodClassifierBaseTInput
            Accord.MachineLearning.VectorMachinesSupportVectorMachineTKernel, TInput
            Accord.Statistics.Models.RegressionGeneralizedLinearRegression
            Accord.Statistics.Models.RegressionProportionalHazards

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

Syntax

Copy

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

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

Request Example View Source

Type Parameters

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

The BinaryLikelihoodClassifierBaseTInput type exposes the following members.

Constructors

	Name	Description
	BinaryLikelihoodClassifierBaseTInput	Initializes a new instance of the BinaryLikelihoodClassifierBaseTInput class

Top

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.)

Top

Methods

	Name	Description
	Decide(TInput)	Computes a class-label decision for a given input. (Inherited from BinaryScoreClassifierBaseTInput.)
	Decide(TInput)	Computes class-label decisions for a given set of input vectors. (Inherited from ClassifierBaseTInput, TClasses.)
	Decide(TInput, Boolean)	Computes class-label decisions for the given input. (Inherited from BinaryClassifierBaseTInput.)
	Decide(TInput, Boolean)	Computes a class-label decision for a given input. (Inherited from BinaryScoreClassifierBaseTInput.)
	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)	Predicts a class label vector for the given input vector, returning the log-likelihood that the input vector belongs to its predicted class.
	LogLikelihood(TInput)	Predicts a class label vector for the given input vector, returning the log-likelihood that the input vector belongs to its predicted class.
	LogLikelihood(TInput, Boolean)	Predicts a class label vector for the given input vector, returning the log-likelihood that the input vector belongs to its predicted class.
	LogLikelihood(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.
	LogLikelihood(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.
	LogLikelihood(TInput, Boolean)	Predicts a class label for each input vector, returning the log-likelihood that each vector belongs to its predicted class.
	LogLikelihood(TInput, Double)	Predicts a class label vector for the given input vectors, returning the log-likelihood that the input vector belongs to its predicted class.
	LogLikelihood(TInput, Double)	Predicts a class label for each input vector, returning the log-likelihood that each vector belongs to its predicted class.
	LogLikelihood(TInput, Int32)	Predicts a class label for each input vector, returning the log-likelihood that each vector belongs to its predicted class.
	LogLikelihood(TInput, Boolean, Double)	Predicts a class label for each input vector, returning the log-likelihood that each vector belongs to its predicted class.
	LogLikelihood(TInput, Double, Double)	Predicts a class label for each input vector, returning the log-likelihood that each vector belongs to its predicted class.
	LogLikelihood(TInput, Int32, Double)	Predicts a class label for each input vector, returning the log-likelihood that each vector belongs to its predicted class.
	LogLikelihoods(TInput)	Computes the log-likelihood that the given input vector belongs to each of the possible classes.
	LogLikelihoods(TInput)	Computes the log-likelihoods that the given input vectors 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, 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, 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-likelihoods that the given input vectors 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, 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, 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, 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 vectors 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, 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)	Probabilitieses the specified input.
	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, 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 vectors 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, 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, 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)	Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
	Probability(TInput)	Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
	Probability(TInput, Boolean)	Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
	Probability(TInput, Double)	Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
	Probability(TInput, Int32)	Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
	Probability(TInput, Boolean)	Predicts a class label for each input vector, returning the probability that each vector belongs to its predicted class.
	Probability(TInput, Double)	Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
	Probability(TInput, Double)	Predicts a class label for each input vector, returning the probability that each vector belongs to its predicted class.
	Probability(TInput, Int32)	Predicts a class label for each input vector, returning the probability that each vector belongs to its predicted class.
	Probability(TInput, Boolean, Double)	Predicts a class label for each input vector, returning the probability that each vector belongs to its predicted class.
	Probability(TInput, Double, Double)	Predicts a class label for each input vector, returning the probability that each vector belongs to its predicted class.
	Probability(TInput, Int32, Double)	Predicts a class label for each input vector, returning the probability that each vector belongs to its predicted class.
	Score(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 BinaryScoreClassifierBaseTInput.)
	Score(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 BinaryScoreClassifierBaseTInput.)
	Score(TInput, Double)	Computes a numerical score measuring the association between the given input vector and each class. (Overrides BinaryScoreClassifierBaseTInputScore(TInput, Double).)
	Score(TInput, Boolean)	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 BinaryScoreClassifierBaseTInput.)
	Score(TInput, Boolean)	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 BinaryScoreClassifierBaseTInput.)
	Score(TInput, Boolean, 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 BinaryScoreClassifierBaseTInput.)
	Scores(TInput)	Computes a numerical score measuring the association between the given input vector and each class. (Inherited from BinaryScoreClassifierBaseTInput.)
	Scores(TInput)	Computes a numerical score measuring the association between the given input vector and each class. (Inherited from BinaryScoreClassifierBaseTInput.)
	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 BinaryScoreClassifierBaseTInput.)
	Scores(TInput, Double)	Computes a numerical score measuring the association between the given input vector and each class. (Inherited from BinaryScoreClassifierBaseTInput.)
	Scores(TInput, Boolean)	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 BinaryScoreClassifierBaseTInput.)
	Scores(TInput, Double)	Computes a numerical score measuring the association between the given input vector and each class. (Inherited from BinaryScoreClassifierBaseTInput.)
	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 BinaryScoreClassifierBaseTInput.)
	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 BinaryScoreClassifierBaseTInput.)
	ToMulticlass	Views this instance as a multi-class generative classifier, giving access to more advanced methods, such as the prediction of integer labels.
	ToMulticlassT	Views this instance as a multi-class generative classifier, giving access to more advanced methods, such as the prediction of integer labels.
	ToMultilabel	Views this instance as a multi-label generative classifier, giving access to more advanced methods, such as the prediction of one-hot vectors.
	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 BinaryClassifierBaseTInput.)
	Transform(TInput, Int32)	Applies the transformation to an input, producing an associated output. (Inherited from BinaryClassifierBaseTInput.)
	Transform(TInput, Boolean)	Applies the transformation to an input, producing an associated output. (Inherited from BinaryClassifierBaseTInput.)
	Transform(TInput, Int32)	Applies the transformation to an input, producing an associated output. (Inherited from BinaryClassifierBaseTInput.)
	Transform(TInput, Int32)	Applies the transformation to an input, producing an associated output. (Inherited from BinaryClassifierBaseTInput.)
	Transform(TInput, Double)	Applies the transformation to a set of input vectors, producing an associated set of output vectors. (Overrides BinaryScoreClassifierBaseTInputTransform(TInput, Double).)
	Transform(TInput, Double)	Applies the transformation to a set of input vectors, producing an associated set of output vectors. (Overrides BinaryScoreClassifierBaseTInputTransform(TInput, Double).)
	Transform(TInput, Double)	Applies the transformation to a set of input vectors, producing an associated set of output vectors. (Overrides BinaryScoreClassifierBaseTInputTransform(TInput, Double).)
	Transform(TInput, TClasses)	Applies the transformation to an input, producing an associated output. (Inherited from ClassifierBaseTInput, TClasses.)

Top

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.)

Top

Reference

Accord.MachineLearning Namespace

BinaryLikelihoodClassifierBaseAddLanguageSpecificTextSet("LST6627B18A_0?cs=&lt;|vb=(Of |cpp=&lt;|fs=&lt;'|nu=(");TInputAddLanguageSpecificTextSet("LST6627B18A_1?cs=&gt;|vb=)|cpp=&gt;|fs=&gt;|nu=)"); Class

Type Parameters

Reference

BinaryLikelihoodClassifierBaseTInput Class