C# Класс Accord.Statistics.Kernels.Sparse.SparseLinear

Наследование: KernelBase, IKernel, ITransform
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Открытые методы

Метод Описание
Clone ( ) : object

Creates a new object that is a copy of the current instance.

Distance ( double x, double y ) : double

Computes the squared distance in feature space between two points given in input space.

Function ( double x, double y ) : double

Sparse Linear kernel function.

Product ( double x, double y ) : double

Computes the product of two vectors given in sparse representation.

SparseLinear ( ) : System

Constructs a new Linear Kernel.

SparseLinear ( double constant ) : System

Constructs a new Linear kernel.

SquaredEuclidean ( double x, double y ) : double

Computes the squared Euclidean distance of two vectors given in sparse representation.

Описание методов

Clone() публичный Метод

Creates a new object that is a copy of the current instance.
public Clone ( ) : object
Результат object

Distance() публичный Метод

Computes the squared distance in feature space between two points given in input space.
public Distance ( double x, double y ) : double
x double Vector x in feature (kernel) space.
y double Vector y in feature (kernel) space.
Результат double

Function() публичный Метод

Sparse Linear kernel function.
public Function ( double x, double y ) : double
x double Sparse vector x in input space.
y double Sparse vector y in input space.
Результат double

Product() публичный статический Метод

Computes the product of two vectors given in sparse representation.
public static Product ( double x, double y ) : double
x double The first vector x.
y double The second vector y.
Результат double

SparseLinear() публичный Метод

Constructs a new Linear Kernel.
public SparseLinear ( ) : System
Результат System

SparseLinear() публичный Метод

Constructs a new Linear kernel.
public SparseLinear ( double constant ) : System
constant double A constant intercept term. Default is 0.
Результат System

SquaredEuclidean() публичный статический Метод

Computes the squared Euclidean distance of two vectors given in sparse representation.
public static SquaredEuclidean ( double x, double y ) : double
x double The first vector x.
y double The second vector y.
Результат double