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added support for cross-validation setting for kernel selection (inco…
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src/shogun/statistical_testing/internals/MaxXValidation.cpp
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/* | ||
* Copyright (c) The Shogun Machine Learning Toolbox | ||
* Written (W) 2013 Heiko Strathmann | ||
* Written (w) 2014 - 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. | ||
*/ | ||
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#include <algorithm> | ||
#include <shogun/lib/SGVector.h> | ||
#include <shogun/kernel/Kernel.h> | ||
#include <shogun/statistical_testing/MMD.h> | ||
#include <shogun/statistical_testing/internals/MaxXValidation.h> | ||
#include <shogun/statistical_testing/internals/KernelManager.h> | ||
#include <shogun/statistical_testing/internals/DataManager.h> | ||
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using namespace shogun; | ||
using namespace internal; | ||
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MaxXValidation::MaxXValidation(KernelManager& km, CMMD* est, const index_t& M, const float64_t& alp) | ||
: KernelSelection(km), estimator(est), num_run(M), alpha(alp) | ||
{ | ||
// TODO write a more meaningful error message | ||
REQUIRE(estimator!=nullptr, "Estimator is not set!\n"); | ||
REQUIRE(kernel_mgr.num_kernels()>0, "Number of kernels is %d!\n", kernel_mgr.num_kernels()); | ||
REQUIRE(num_run>0, "Number of runs is %d!\n", num_run); | ||
REQUIRE(alpha>=0.0 && alpha<=1.0, "Threshold is %f!\n", alpha); | ||
} | ||
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MaxXValidation::~MaxXValidation() | ||
{ | ||
} | ||
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void MaxXValidation::compute_measures(SGVector<float64_t>& measures, SGVector<index_t>& term_counters) | ||
{ | ||
const size_t num_kernels=kernel_mgr.num_kernels(); | ||
for (size_t i=0; i<num_kernels; ++i) | ||
{ | ||
auto kernel=kernel_mgr.kernel_at(i); | ||
estimator->set_kernel(kernel); | ||
bool rejected=estimator->compute_p_value(estimator->compute_statistic())<alpha; | ||
auto delta=measures[i]-rejected; | ||
measures[i]=delta/term_counters[i]++; | ||
estimator->cleanup(); | ||
} | ||
} | ||
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CKernel* MaxXValidation::select_kernel() | ||
{ | ||
auto& dm=estimator->get_data_manager(); | ||
dm.set_xvalidation_mode(true); | ||
auto existing_kernel=estimator->get_kernel(); | ||
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const index_t N=dm.get_num_folds(); | ||
// TODO write a more meaningful error message | ||
REQUIRE(N!=0, "Number of folds is not set!\n"); | ||
SG_SINFO("Performing %d fold cross-validattion!\n", N); | ||
// train mode is already ON by now! set by the caller | ||
SGVector<float64_t> measures(kernel_mgr.num_kernels()); | ||
std::fill(measures.data(), measures.data()+measures.size(), 0); | ||
SGVector<index_t> term_counters(measures.size()); | ||
std::fill(term_counters.data(), term_counters.data()+term_counters.size(), 1); | ||
for (auto i=0; i<num_run; ++i) | ||
{ | ||
for (auto j=0; j<N; ++j) | ||
{ | ||
dm.use_fold(j); | ||
compute_measures(measures, term_counters); | ||
} | ||
} | ||
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estimator->set_kernel(existing_kernel); | ||
dm.set_xvalidation_mode(false); | ||
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auto min_element=std::min_element(measures.vector, measures.vector+measures.vlen); | ||
auto min_idx=std::distance(measures.vector, min_element); | ||
SG_SDEBUG("Selected kernel at %d position!\n", min_idx); | ||
return kernel_mgr.kernel_at(min_idx); | ||
} |
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/* | ||
* Copyright (c) The Shogun Machine Learning Toolbox | ||
* Written (W) 2013 Heiko Strathmann | ||
* Written (w) 2014 - 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. | ||
*/ | ||
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#ifndef MAX_XVALIDATIN_H__ | ||
#define MAX_XVALIDATIN_H__ | ||
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#include <shogun/lib/common.h> | ||
#include <shogun/statistical_testing/internals/KernelSelection.h> | ||
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namespace shogun | ||
{ | ||
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class CKernel; | ||
class CMMD; | ||
template <typename T> class SGVector; | ||
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namespace internal | ||
{ | ||
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class MaxXValidation : public KernelSelection | ||
{ | ||
public: | ||
MaxXValidation(KernelManager&, CMMD*, const index_t&, const float64_t&); | ||
MaxXValidation(const MaxXValidation& other)=delete; | ||
~MaxXValidation(); | ||
MaxXValidation& operator=(const MaxXValidation& other)=delete; | ||
virtual CKernel* select_kernel() override; | ||
protected: | ||
void compute_measures(SGVector<float64_t>&, SGVector<index_t>&); | ||
CMMD* estimator; | ||
const index_t num_run; | ||
const float64_t alpha; | ||
}; | ||
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} | ||
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} | ||
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#endif // MAX_XVALIDATIN_H__ |