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MulticlassScoreClassifierBaseTInput Class
Base class for score-based multi-class classifiers.
Inheritance Hierarchy
SystemObject
  Accord.MachineLearningTransformBaseTInput, Int32
    Accord.MachineLearningClassifierBaseTInput, Int32
      Accord.MachineLearningMulticlassClassifierBaseTInput
        Accord.MachineLearningMulticlassScoreClassifierBaseTInput
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Namespace:  Accord.MachineLearning
Assembly:  Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0
Syntax
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[SerializableAttribute]
public abstract class MulticlassScoreClassifierBase<TInput> : MulticlassClassifierBase<TInput>, 
	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[]>, IClassifier<TInput, int>, IClassifier, 
	ITransform<TInput, int>, ICovariantTransform<TInput, int>, ITransform, 
	IMulticlassScoreClassifier<TInput, double>, IMulticlassOutScoreClassifier<TInput, double>, 
	IMulticlassScoreClassifierBase<TInput, double>, IMultilabelOutScoreClassifier<TInput, double>, 
	IMultilabelScoreClassifierBase<TInput, double>, IMulticlassRefScoreClassifier<TInput, double[]>, 
	IMultilabelRefScoreClassifier<TInput, double[]>, IMultilabelScoreClassifierBase<TInput, double[]>, 
	IClassifier<TInput, double>, ITransform<TInput, double>, 
	ICovariantTransform<TInput, double>, IMulticlassRefScoreClassifier<TInput, bool[]>, 
	IMultilabelRefScoreClassifier<TInput, bool[]>, IMultilabelScoreClassifierBase<TInput, bool[]>, 
	IMultilabelScoreClassifier<TInput>, IMultilabelScoreClassifier<TInput, int>, IMultilabelScoreClassifier<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[]>, 
	IMulticlassClassifier<TInput>, IMulticlassClassifier<TInput, int>, IMulticlassClassifier<TInput, double>
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Type Parameters

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

The MulticlassScoreClassifierBaseTInput type exposes the following members.

Constructors
  NameDescription
Protected methodMulticlassScoreClassifierBaseTInput
Initializes a new instance of the MulticlassScoreClassifierBaseTInput 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.
(Overrides ClassifierBaseTInput, TClassesDecide(TInput).)
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.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
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).
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).
Public methodScore(TInput, Double)
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.
Public methodScore(TInput, Int32)
Computes a numerical score measuring the association between the given input vector and a given classIndex.
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.
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).
Public methodScore(TInput, 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.
Public methodScore(TInput, Int32)
Computes a numerical score measuring the association between the given input vector and a given classIndex.
Public methodScore(TInput, Int32)
Computes a numerical score measuring the association between the given input vector and a given classIndex.
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.
Public methodScore(TInput, Double, 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.
Public methodScore(TInput, Int32, Double)
Computes a numerical score measuring the association between the given input vector and a given classIndex.
Public methodScore(TInput, Int32, Double)
Computes a numerical score measuring the association between the given input vector and a given classIndex.
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.
Public methodScores(TInput)
Computes a numerical score measuring the association between the given input vector and each class.
Public methodScores(TInput)
Computes a numerical score measuring the association between the given input vector and each class.
Public methodScores(TInput, 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.
Public methodScores(TInput, Double)
Computes a numerical score measuring the association between the given input vector and each class.
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.
Public methodScores(TInput, 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.
Public methodScores(TInput, Double)
Computes a numerical score measuring the association between the given input vector and each class.
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.
Public methodScores(TInput, Double, 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.
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.
Public methodScores(TInput, Double, 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.
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.
Public methodToMulticlass
Views this instance as a multi-class generative classifier.
Public methodToMulticlassT
Views this instance as a multi-class generative classifier.
Public methodToMultilabel
Views this instance as a multi-label distance 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 MulticlassClassifierBaseTInputTransform(TInput, Double).)
Public methodTransform(TInput, Double)
Applies the transformation to an input, producing an associated output.
(Overrides MulticlassClassifierBaseTInputTransform(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 MethodTo(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.)
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.)
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See Also
Inheritance Hierarchy
SystemObject
  Accord.MachineLearningTransformBaseTInput, Int32
    Accord.MachineLearningClassifierBaseTInput, Int32
      Accord.MachineLearningMulticlassClassifierBaseTInput
        Accord.MachineLearningMulticlassScoreClassifierBaseTInput
          Accord.MachineLearningBaseKNearestNeighborsTModel, TInput, TDistance
          Accord.MachineLearningKMeansClusterCollection
          Accord.MachineLearningKMedoidsClusterCollectionT
          Accord.MachineLearningKModesClusterCollectionT
          Accord.MachineLearningMinimumMeanDistanceClassifier
          Accord.MachineLearningMulticlassLikelihoodClassifierBaseTInput
          Accord.Statistics.AnalysisKernelDiscriminantAnalysisPipeline
          Accord.Statistics.AnalysisLinearDiscriminantAnalysisPipeline