#include <shark/Data/Dataset.h>#include <shark/Core/Random.h>#include <shark/Algorithms/Trainers/NormalizeKernelUnitVariance.h>#include <shark/Models/Kernels/GaussianRbfKernel.h>#include <shark/Models/Kernels/WeightedSumKernel.h>#include <shark/Models/Kernels/SubrangeKernel.h>#include <shark/Models/Kernels/MklKernel.h>#include <shark/Models/Kernels/LinearKernel.h>#include <shark/Models/Kernels/DiscreteKernel.h>#include <shark/Models/Kernels/PolynomialKernel.h>#include <boost/fusion/algorithm/iteration/fold.hpp>#include <boost/fusion/include/as_vector.hpp>Go to the source code of this file.
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| shark | |
| AbstractMultiObjectiveOptimizer. | |
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| int | main (int argc, char **argv) |
| int main | ( | int | argc, |
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Definition at line 43 of file MklKernelTutorial.cpp.
References shark::createDataFromRange(), shark::Data< Type >::element(), shark::ScaledKernel< InputType >::eval(), shark::WeightedSumKernel< InputType >::eval(), shark::ScaledKernel< InputType >::factor(), shark::random::globalRng, shark::WeightedSumKernel< InputType >::isAdaptive(), shark::NormalizeKernelUnitVariance< InputType >::mean(), shark::WeightedSumKernel< InputType >::numberOfParameters(), shark::WeightedSumKernel< InputType >::parameterVector(), shark::WeightedSumKernel< InputType >::setAdaptive(), shark::WeightedSumKernel< InputType >::setAdaptiveAll(), shark::WeightedSumKernel< InputType >::setParameterVector(), shark::NormalizeKernelUnitVariance< InputType >::trace(), shark::NormalizeKernelUnitVariance< InputType >::train(), and shark::random::uni().