The Epanechnikov kernel, defined as.
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| EpanechnikovKernel (const double bandwidth=1.0) |
| Instantiate the Epanechnikov kernel with the given bandwidth (default 1.0). More...
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template<typename VecTypeA , typename VecTypeB > |
double | ConvolutionIntegral (const VecTypeA &a, const VecTypeB &b) |
| Obtains the convolution integral [integral of K(||x-a||) K(||b-x||) dx] for the two vectors. More...
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template<typename VecTypeA , typename VecTypeB > |
double | Evaluate (const VecTypeA &a, const VecTypeB &b) const |
| Evaluate the Epanechnikov kernel on the given two inputs. More...
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double | Evaluate (const double distance) const |
| Evaluate the Epanechnikov kernel given that the distance between the two input points is known. More...
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double | Gradient (const double distance) const |
| Evaluate the Gradient of Epanechnikov kernel given that the distance between the two input points is known. More...
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double | GradientForSquaredDistance (const double distanceSquared) const |
| Evaluate the Gradient of Epanechnikov kernel given that the squared distance between the two input points is known. More...
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double | Normalizer (const size_t dimension) |
| Compute the normalizer of this Epanechnikov kernel for the given dimension. More...
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template<typename Archive > |
void | Serialize (Archive &ar, const unsigned int version) |
| Serialize the kernel. More...
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The Epanechnikov kernel, defined as.
where
is the bandwidth the of the kernel (defaults to 1.0).
Definition at line 30 of file epanechnikov_kernel.hpp.
Instantiate the Epanechnikov kernel with the given bandwidth (default 1.0).
- Parameters
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bandwidth | Bandwidth of the kernel. |
Definition at line 38 of file epanechnikov_kernel.hpp.
double ConvolutionIntegral |
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const VecTypeA & |
a, |
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const VecTypeB & |
b |
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Obtains the convolution integral [integral of K(||x-a||) K(||b-x||) dx] for the two vectors.
- Template Parameters
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VecType | Type of vector (arma::vec, arma::spvec should be expected). |
- Parameters
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a | First vector. |
b | Second vector. |
- Returns
- the convolution integral value.
double Evaluate |
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const VecTypeA & |
a, |
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const VecTypeB & |
b |
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) |
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Evaluate the Epanechnikov kernel on the given two inputs.
- Template Parameters
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VecTypeA | Type of first vector. |
VecTypeB | Type of second vector. |
- Parameters
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a | One input vector. |
b | The other input vector. |
double Evaluate |
( |
const double |
distance | ) |
const |
Evaluate the Epanechnikov kernel given that the distance between the two input points is known.
double Gradient |
( |
const double |
distance | ) |
const |
Evaluate the Gradient of Epanechnikov kernel given that the distance between the two input points is known.
double GradientForSquaredDistance |
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const double |
distanceSquared | ) |
const |
Evaluate the Gradient of Epanechnikov kernel given that the squared distance between the two input points is known.
double Normalizer |
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const size_t |
dimension | ) |
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Compute the normalizer of this Epanechnikov kernel for the given dimension.
- Parameters
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dimension | Dimension to calculate the normalizer for. |
void Serialize |
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Archive & |
ar, |
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const unsigned int |
version |
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) |
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The documentation for this class was generated from the following file: