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MMD.h
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MMD.h
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/*
* Copyright (c) The Shogun Machine Learning Toolbox
* Written (w) 2016 Soumyajit De
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice, this
* list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
* ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
* The views and conclusions contained in the software and documentation are those
* of the authors and should not be interpreted as representing official policies,
* either expressed or implied, of the Shogun Development Team.
*/
#ifndef MMD_H_
#define MMD_H_
#include <utility>
#include <memory>
#include <functional>
#include <shogun/statistical_testing/TwoSampleTest.h>
namespace shogun
{
class CKernel;
template <typename> class SGVector;
template <typename> class SGMatrix;
class CKernelSelectionStrategy;
enum EKernelSelectionMethod : uint32_t;
namespace internal
{
class KernelManager;
class MaxTestPower;
class MaxCrossValidation;
class WeightedMaxTestPower;
}
enum EStatisticType : uint32_t
{
ST_UNBIASED_FULL,
ST_UNBIASED_INCOMPLETE,
ST_BIASED_FULL
};
enum EVarianceEstimationMethod : uint32_t
{
VEM_DIRECT,
VEM_PERMUTATION
};
enum ENullApproximationMethod : uint32_t
{
NAM_PERMUTATION,
NAM_MMD1_GAUSSIAN,
NAM_MMD2_SPECTRUM,
NAM_MMD2_GAMMA
};
class CMMD : public CTwoSampleTest
{
friend class internal::MaxTestPower;
friend class internal::WeightedMaxTestPower;
friend class internal::MaxCrossValidation;
public:
typedef std::function<float32_t(SGMatrix<float32_t>)> operation;
CMMD();
virtual ~CMMD();
void set_kernel_selection_strategy(EKernelSelectionMethod method);
void set_kernel_selection_strategy(EKernelSelectionMethod method, bool weighted);
void set_kernel_selection_strategy(EKernelSelectionMethod method, index_t num_runs, index_t num_folds, float64_t alpha);
CKernelSelectionStrategy* get_kernel_selection_strategy() const;
void add_kernel(CKernel *kernel);
void select_kernel();
void set_train_test_ratio(float64_t ratio);
virtual float64_t compute_statistic();
virtual float64_t compute_variance();
virtual SGVector<float64_t> sample_null();
void use_gpu(bool gpu);
void cleanup();
void set_statistic_type(EStatisticType stype);
const EStatisticType get_statistic_type() const;
void set_variance_estimation_method(EVarianceEstimationMethod vmethod);
const EVarianceEstimationMethod get_variance_estimation_method() const;
void set_num_null_samples(index_t null_samples);
const index_t get_num_null_samples() const;
void set_null_approximation_method(ENullApproximationMethod nmethod);
const ENullApproximationMethod get_null_approximation_method() const;
virtual const char* get_name() const;
protected:
virtual const operation get_direct_estimation_method() const=0;
virtual const float64_t normalize_statistic(float64_t statistic) const=0;
virtual const float64_t normalize_variance(float64_t variance) const=0;
bool use_gpu() const;
private:
struct Self;
std::unique_ptr<Self> self;
virtual std::pair<float64_t, float64_t> compute_statistic_variance();
std::pair<SGVector<float64_t>, SGMatrix<float64_t> > compute_statistic_and_Q(const internal::KernelManager&);
};
}
#endif // MMD_H_