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Kernel Class

Extension methods for kernel functions.
Inheritance Hierarchy
SystemObject
  Accord.Statistics.KernelsKernel

Namespace:  Accord.Statistics.Kernels
Assembly:  Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0
Syntax
public static class Kernel
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The Kernel type exposes the following members.

Methods
  NameDescription
Public methodStatic memberCenter(Double, Double)
Centers the given kernel matrix K.
Public methodStatic memberCenter(Double, Double, Double, Double)
Centers the given kernel matrix K.
Public methodStatic memberCenter(Double, Double, Double, Double)
Centers the given kernel matrix K.
Public methodStatic memberCenter(Double, Double, Double, Double)
Centers the given kernel matrix K.
Public methodStatic memberDistancesT(T, Double, Int32)
Computes the set of all distances between all points in a random subset of the data.
Public methodStatic memberDistancesTKernel, TData(TKernel, TData, Int32)
Computes the set of all distances between all points in a random subset of the data.
Public methodStatic memberEstimateComplexity(Double)
Estimates the complexity parameter C, present in many SVM algorithms, for a given kernel and a given data set by summing every element on the diagonal of the kernel matrix and using an heuristic based on it.
Public methodStatic memberEstimateComplexity(Double, Int32)
Estimates the complexity parameter C, present in many SVM algorithms, for a given kernel and an unbalanced data set by summing every element on the diagonal of the kernel matrix and using an heuristic based on it.
Public methodStatic memberEstimateComplexityTKernel, TInput(TKernel, TInput)
Estimates the complexity parameter C, present in many SVM algorithms, for a given kernel and a given data set by summing every element on the diagonal of the kernel matrix and using an heuristic based on it.
Public methodStatic memberEstimateComplexityTKernel, TInput(TKernel, TInput, Int32)
Estimates the complexity parameter C, present in many SVM algorithms, for a given kernel and an unbalanced data set by summing every element on the diagonal of the kernel matrix and using an heuristic based on it.
Public methodStatic memberToJaggedTKernel, TInput
Creates the Gram matrix from the given vectors.
Public methodStatic memberToJagged2TKernel, TInput
Creates the Gram matrix containing all dot products in feature (kernel) space between each vector in x and the ones in y.
Public methodStatic memberToMatrixTKernel, TInput
Creates the Gram matrix from the given vectors.
Public methodStatic memberToMatrix2TKernel, TInput
Creates the Gram matrix containing all dot products in feature (kernel) space between each vector in x and the ones in y.
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