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Base.h
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Base.h
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/*
* Copyright (c) The Shogun Machine Learning Toolbox
* Written (w) 2016 Heiko Strathmann
* 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 KERNEL_EXP_FAMILY_IMPL_BASE__
#define KERNEL_EXP_FAMILY_IMPL_BASE__
#include <shogun/lib/config.h>
#include <shogun/lib/common.h>
#include <shogun/lib/SGMatrix.h>
#include <shogun/lib/SGVector.h>
#include <utility>
#include "kernel/Base.h"
namespace shogun
{
namespace kernel_exp_family_impl
{
namespace kernel
{
class Base;
};
class Base
{
public :
Base(SGMatrix<float64_t> data, kernel::Base* kernel, float64_t lambda);
virtual ~Base();
// for evaluation
void set_test_data(SGMatrix<float64_t> X);
void set_test_data(SGVector<float64_t> x);
void fit();
float64_t log_pdf(SGVector<float64_t> x);
SGVector<float64_t> log_pdf(SGMatrix<float64_t> X);
SGVector<float64_t> grad(SGVector<float64_t> x);
SGMatrix<float64_t> hessian(SGVector<float64_t> x);
SGVector<float64_t> get_alpha_beta() const { return m_alpha_beta; }
index_t get_num_dimensions() const;
index_t get_num_lhs() const;
index_t get_num_rhs() const;
virtual std::pair<SGMatrix<float64_t>, SGVector<float64_t>> build_system() const=0;
virtual float64_t log_pdf(index_t idx_test) const=0;
virtual SGVector<float64_t> grad(index_t idx_test) const=0;
virtual SGMatrix<float64_t> hessian(index_t idx_test) const=0;
protected:
virtual void solve_and_store(const SGMatrix<float64_t>& A, const SGVector<float64_t>& b);
kernel::Base* m_kernel;
float64_t m_lambda;
SGVector<float64_t> m_alpha_beta;
};
};
}
#endif // KERNEL_EXP_FAMILY_IMPL_BASE__