Definition at line 32 of file spherical_kernel.hpp.
mlpack::kernel::SphericalKernel::SphericalKernel |
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mlpack::kernel::SphericalKernel::SphericalKernel |
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double |
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template<typename VecType >
double mlpack::kernel::SphericalKernel::ConvolutionIntegral |
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const VecType & |
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const VecType & |
b |
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Obtains the convolution integral [integral K(||x-a||)K(||b-x||)dx] for the two vectors.
In this case, because our simple example kernel has no internal parameters, we can declare the function static. For a more complex example which cannot be declared static, see the GaussianKernel, which stores an internal parameter.
- 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.
Definition at line 62 of file spherical_kernel.hpp.
References bandwidth, mlpack::metric::LMetric< Power, TakeRoot >::Evaluate(), mlpack::Log::Fatal, and Normalizer().
template<typename VecType >
double mlpack::kernel::SphericalKernel::Evaluate |
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const VecType & |
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const VecType & |
b |
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double mlpack::kernel::SphericalKernel::Evaluate |
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double |
t | ) |
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double mlpack::kernel::SphericalKernel::Normalizer |
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size_t |
dimension | ) |
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std::string mlpack::kernel::SphericalKernel::ToString |
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const |
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double mlpack::kernel::SphericalKernel::bandwidth |
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double mlpack::kernel::SphericalKernel::bandwidthSquared |
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The documentation for this class was generated from the following file: