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src
shogun
kernel
LinearKernel.cpp
Go to the documentation of this file.
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/*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation; either version 3 of the License, or
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* (at your option) any later version.
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*
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* Written (W) 1999-2010 Soeren Sonnenburg
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* Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
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* Copyright (C) 2010 Berlin Institute of Technology
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*/
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#include <
shogun/lib/common.h
>
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#include <
shogun/io/SGIO.h
>
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#include <
shogun/features/Features.h
>
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#include <
shogun/features/DotFeatures.h
>
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#include <
shogun/kernel/LinearKernel.h
>
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using namespace
shogun;
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CLinearKernel::CLinearKernel
()
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:
CDotKernel
(0)
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{
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properties
|=
KP_LINADD
;
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}
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CLinearKernel::CLinearKernel
(
CDotFeatures
* l,
CDotFeatures
* r)
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:
CDotKernel
(0)
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{
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properties
|=
KP_LINADD
;
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init
(l,r);
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}
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CLinearKernel::~CLinearKernel
()
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{
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cleanup
();
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}
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bool
CLinearKernel::init(
CFeatures
* l,
CFeatures
* r)
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{
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CDotKernel::init(l, r);
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return
init_normalizer
();
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}
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void
CLinearKernel::cleanup
()
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{
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delete_optimization
();
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CKernel::cleanup
();
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}
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void
CLinearKernel::add_to_normal
(int32_t idx,
float64_t
weight)
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{
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((
CDotFeatures
*)
lhs
)->add_to_dense_vec(
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normalizer
->
normalize_lhs
(weight, idx), idx,
normal
.
vector
,
normal
.
size
());
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set_is_initialized
(
true
);
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}
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bool
CLinearKernel::init_optimization
(
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int32_t num_suppvec, int32_t* sv_idx,
float64_t
* alphas)
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{
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clear_normal
();
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for
(int32_t i=0; i<num_suppvec; i++)
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add_to_normal
(sv_idx[i], alphas[i]);
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set_is_initialized
(
true
);
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return
true
;
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}
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bool
CLinearKernel::init_optimization
(
CKernelMachine
* km)
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{
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clear_normal
();
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int32_t num_suppvec=km->
get_num_support_vectors
();
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for
(int32_t i=0; i<num_suppvec; i++)
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add_to_normal
(km->
get_support_vector
(i), km->
get_alpha
(i));
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set_is_initialized
(
true
);
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return
true
;
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}
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bool
CLinearKernel::delete_optimization
()
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{
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normal
=
SGVector<float64_t>
();
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set_is_initialized
(
false
);
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return
true
;
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}
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float64_t
CLinearKernel::compute_optimized
(int32_t idx)
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{
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ASSERT
(
get_is_initialized
())
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float64_t
result = ((
CDotFeatures
*)
rhs
)->
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dense_dot(idx,
normal
.
vector
,
normal
.
size
());
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return
normalizer
->
normalize_rhs
(result, idx);
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}
SHOGUN
Machine Learning Toolbox - Documentation