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KernelSupportVectorMachine Class

Note: This API is now obsolete.

Obsolete.
Inheritance Hierarchy
SystemObject
  Accord.MachineLearningTransformBaseDouble, Boolean
    Accord.MachineLearningClassifierBaseDouble, Boolean
      Accord.MachineLearningBinaryClassifierBaseDouble
        Accord.MachineLearningBinaryScoreClassifierBaseDouble
          Accord.MachineLearningBinaryLikelihoodClassifierBaseDouble
            Accord.MachineLearning.VectorMachinesSupportVectorMachineIKernelDouble, Double
              Accord.MachineLearning.VectorMachinesSupportVectorMachineIKernelDouble
                Accord.MachineLearning.VectorMachinesKernelSupportVectorMachine

Namespace:  Accord.MachineLearning.VectorMachines
Assembly:  Accord.MachineLearning (in Accord.MachineLearning.dll) Version: 3.5.0
Syntax
[SerializableAttribute]
[ObsoleteAttribute("Please use SupportVectorMachine<TKernel>.")]
public class KernelSupportVectorMachine : SupportVectorMachine<IKernel<double[]>>, 
	ISupportVectorMachine<double[]>, IBinaryLikelihoodClassifier<double[]>, IBinaryScoreClassifier<double[]>, 
	IBinaryClassifier<double[]>, IMulticlassClassifier<double[]>, IMultilabelClassifier<double[]>, 
	IMultilabelClassifier<double[], int[]>, IClassifier<double[], int[]>, 
	ITransform<double[], int[]>, ITransform, IMultilabelClassifier<double[], bool[]>, 
	IClassifier<double[], bool[]>, ITransform<double[], bool[]>, 
	IMultilabelClassifier<double[], double[]>, IClassifier<double[], double[]>, 
	ITransform<double[], double[]>, IMulticlassClassifier<double[], int>, 
	IClassifier<double[], int>, ITransform<double[], int>, 
	IMulticlassClassifier<double[], double>, IClassifier<double[], double>, 
	ITransform<double[], double>, IClassifier<double[], bool>, 
	ITransform<double[], bool>, IMulticlassOutScoreClassifier<double[], bool>, 
	IMulticlassScoreClassifier<double[], bool>, IMultilabelOutScoreClassifier<double[], bool>, 
	IMultilabelScoreClassifier<double[], bool>, IMulticlassScoreClassifier<double[]>, 
	IMulticlassOutScoreClassifier<double[], int>, IMulticlassScoreClassifier<double[], int>, 
	IMultilabelOutScoreClassifier<double[], int>, IMultilabelScoreClassifier<double[], int>, 
	IMulticlassOutScoreClassifier<double[], double>, IMulticlassScoreClassifier<double[], double>, 
	IMultilabelOutScoreClassifier<double[], double>, IMultilabelScoreClassifier<double[], double>, 
	IMulticlassRefScoreClassifier<double[], int[]>, IMultilabelRefScoreClassifier<double[], int[]>, 
	IMultilabelScoreClassifier<double[], int[]>, IMulticlassRefScoreClassifier<double[], bool[]>, 
	IMultilabelRefScoreClassifier<double[], bool[]>, IMultilabelScoreClassifier<double[], bool[]>, 
	IMulticlassRefScoreClassifier<double[], double[]>, IMultilabelRefScoreClassifier<double[], double[]>, 
	IMultilabelScoreClassifier<double[], double[]>, IMultilabelScoreClassifier<double[]>, 
	IMulticlassOutLikelihoodClassifier<double[], bool>, IMultilabelOutLikelihoodClassifier<double[], bool>, 
	IMultilabelLikelihoodClassifier<double[], bool>, IMulticlassLikelihoodClassifier<double[], bool>, 
	IMulticlassLikelihoodClassifier<double[]>, IMulticlassOutLikelihoodClassifier<double[], int>, 
	IMultilabelOutLikelihoodClassifier<double[], int>, IMultilabelLikelihoodClassifier<double[], int>, 
	IMulticlassLikelihoodClassifier<double[], int>, IMulticlassOutLikelihoodClassifier<double[], double>, 
	IMultilabelOutLikelihoodClassifier<double[], double>, IMultilabelLikelihoodClassifier<double[], double>, 
	IMulticlassLikelihoodClassifier<double[], double>, IMulticlassRefLikelihoodClassifier<double[], int[]>, 
	IMultilabelRefLikelihoodClassifier<double[], int[]>, IMultilabelLikelihoodClassifier<double[], int[]>, 
	IMulticlassRefLikelihoodClassifier<double[], bool[]>, IMultilabelRefLikelihoodClassifier<double[], bool[]>, 
	IMultilabelLikelihoodClassifier<double[], bool[]>, IMulticlassRefLikelihoodClassifier<double[], double[]>, 
	IMultilabelRefLikelihoodClassifier<double[], double[]>, IMultilabelLikelihoodClassifier<double[], double[]>, 
	IMultilabelLikelihoodClassifier<double[]>
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The KernelSupportVectorMachine type exposes the following members.

Constructors
Properties
  NameDescription
Public propertyInputs Obsolete.
Gets the number of inputs accepted by this machine.
(Inherited from SupportVectorMachineTKernel, TInput.)
Public propertyIsCompact Obsolete.
Obsolete.
(Inherited from SupportVectorMachineTKernel, TInput.)
Public propertyIsProbabilistic
Gets whether this machine has been calibrated to produce probabilistic outputs (through the Probability(TInput) method).
(Inherited from SupportVectorMachineTKernel, TInput.)
Public propertyKernel
Obsolete.
Public propertyNumberOfInputs
Gets the number of inputs accepted by the model.
(Inherited from TransformBaseTInput, TOutput.)
Public propertyNumberOfOutputs
Gets the number of outputs generated by the model.
(Inherited from TransformBaseTInput, TOutput.)
Public propertySupportVectors
Gets or sets the collection of support vectors used by this machine.
(Inherited from SupportVectorMachineTKernel, TInput.)
Public propertyThreshold
Gets or sets the threshold (bias) term for this machine.
(Inherited from SupportVectorMachineTKernel, TInput.)
Public propertyWeights
Gets or sets the collection of weights used by this machine.
(Inherited from SupportVectorMachineTKernel, TInput.)
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Methods
  NameDescription
Public methodClone
Obsolete.
(Overrides SupportVectorMachineTKernelClone.)
Public methodCompress
If this machine has a linear kernel, compresses all support vectors into a single parameter vector.
(Inherited from SupportVectorMachineTKernel, TInput.)
Public methodCompute(TInput) Obsolete.
Computes the given input to produce the corresponding output.
(Inherited from SupportVectorMachineTKernel, TInput.)
Public methodCompute(TInput, Double) Obsolete.
Computes the given input to produce the corresponding output.
(Inherited from SupportVectorMachineTKernel, TInput.)
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 SupportVectorMachineTKernel, TInput.)
Public methodDecide(TInput, Boolean)
Computes class-label decisions for the given input.
(Inherited from BinaryClassifierBaseTInput.)
Public methodDecide(TInput, TClasses)
Computes a class-label decision for a given input.
(Inherited from ClassifierBaseTInput, TClasses.)
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)
Predicts a class label vector for the given input vector, returning the log-likelihood that the input vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodLogLikelihood(TInput)
Predicts a class label vector for the given input vector, returning the log-likelihood that the input vector belongs to its predicted class.
(Inherited from SupportVectorMachineTKernel, TInput.)
Public methodLogLikelihood(TInput, Boolean)
Predicts a class label for each input vector, returning the log-likelihood that each vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
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.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodLogLikelihood(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.
(Inherited from SupportVectorMachineTKernel, TInput.)
Public methodLogLikelihood(TInput, Boolean, Double)
Predicts a class label for each input vector, returning the log-likelihood that each vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodLogLikelihoods(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.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodLogLikelihoods(TInput, Boolean)
Predicts a class label vector for each input vector, returning the log-likelihoods of the input vector belonging to each possible class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodLogLikelihoods(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.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodLogLikelihoods(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.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodProbabilities(TInput, Boolean)
Predicts a class label vector for the given input vector, returning the probabilities of the input vector belonging to each possible class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodProbabilities(TInput, Boolean)
Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodProbabilities(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.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodProbabilities(TInput, Boolean, Double)
Predicts a class label vector for each input vector, returning the probabilities of the input vector belonging to each possible class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodProbability(TInput)
Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodProbability(TInput)
Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodProbability(TInput, Boolean)
Predicts a class label for the given input vector, returning the probability that the input vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodProbability(TInput, Boolean)
Predicts a class label for each input vector, returning the probability that each vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
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.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodProbability(TInput, Boolean, Double)
Predicts a class label for each input vector, returning the probability that each vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
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 BinaryScoreClassifierBaseTInput.)
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 SupportVectorMachineTKernel, TInput.)
Public methodScore(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.)
Public methodScore(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.)
Public methodScore(TInput, Double)
Computes a numerical score measuring the association between the given input vector and each class.
(Inherited from BinaryScoreClassifierBaseTInput.)
Public methodScore(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.)
Public methodScores(TInput)
Computes a numerical score measuring the association between the given input vector and each class.
(Inherited from BinaryScoreClassifierBaseTInput.)
Public methodScores(TInput)
Computes a numerical score measuring the association between the given input vector and each class.
(Inherited from BinaryScoreClassifierBaseTInput.)
Public methodScores(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.)
Public methodScores(TInput, Double)
Computes a numerical score measuring the association between the given input vector and each class.
(Inherited from BinaryScoreClassifierBaseTInput.)
Public methodScores(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.)
Public methodScores(TInput, Double)
Computes a numerical score measuring the association between the given input vector and each class.
(Inherited from BinaryScoreClassifierBaseTInput.)
Public methodScores(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.)
Public methodScores(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.)
Public methodToMulticlass
Views this instance as a multi-class generative classifier, giving access to more advanced methods, such as the prediction of integer labels.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
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.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
Public methodToWeights
Converts a Linear-kernel machine into an array of linear coefficients. The first position in the array is the Threshold value. If this machine is not linear, an exception will be thrown.
(Inherited from SupportVectorMachineTKernel.)
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, Boolean)
Applies the transformation to an input, producing an associated output.
(Inherited from BinaryClassifierBaseTInput.)
Public methodTransform(TInput, Int32)
Applies the transformation to an input, producing an associated output.
(Inherited from BinaryClassifierBaseTInput.)
Public methodTransform(TInput, Boolean)
Applies the transformation to an input, producing an associated output.
(Inherited from BinaryClassifierBaseTInput.)
Public methodTransform(TInput, Int32)
Applies the transformation to an input, producing an associated output.
(Inherited from BinaryClassifierBaseTInput.)
Public methodTransform(TInput, Int32)
Applies the transformation to an input, producing an associated output.
(Inherited from BinaryClassifierBaseTInput.)
Public methodTransform(TInput, Double)
Applies the transformation to a set of input vectors, producing an associated set of output vectors.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodTransform(TInput, Double)
Applies the transformation to a set of input vectors, producing an associated set of output vectors.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodTransform(TInput, Double)
Applies the transformation to a set of input vectors, producing an associated set of output vectors.
(Inherited from BinaryLikelihoodClassifierBaseTInput.)
Public methodTransform(TInput, TClasses)
Applies the transformation to an input, producing an associated output.
(Inherited from ClassifierBaseTInput, TClasses.)
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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