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src
shogun
statistics
LinearTimeMMD.h
Go to the documentation of this file.
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/*
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* Copyright (c) The Shogun Machine Learning Toolbox
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* Written (w) 2012-2013 Heiko Strathmann
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* Written (w) 2014 Soumyajit De
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice, this
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* list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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* ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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* The views and conclusions contained in the software and documentation are those
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* of the authors and should not be interpreted as representing official policies,
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* either expressed or implied, of the Shogun Development Team.
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*/
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#ifndef LINEAR_TIME_MMD_H_
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#define LINEAR_TIME_MMD_H_
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#include <
shogun/statistics/StreamingMMD.h
>
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namespace
shogun
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{
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class
CStreamingFeatures;
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class
CFeatures;
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class
CLinearTimeMMD
:
public
CStreamingMMD
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{
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public
:
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CLinearTimeMMD
();
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CLinearTimeMMD
(
CKernel
* kernel,
CStreamingFeatures
* p,
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CStreamingFeatures
* q,
index_t
m,
index_t
blocksize=10000);
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virtual
~CLinearTimeMMD
();
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virtual
void
compute_statistic_and_variance
(
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SGVector<float64_t>
& statistic,
SGVector<float64_t>
& variance,
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bool
multiple_kernels=
false
);
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virtual
void
compute_statistic_and_Q
(
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SGVector<float64_t>
& statistic,
SGMatrix<float64_t>
& Q);
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virtual
EStatisticType
get_statistic_type
()
const
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{
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return
S_LINEAR_TIME_MMD
;
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}
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virtual
const
char
*
get_name
()
const
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{
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return
"LinearTimeMMD"
;
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}
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protected
:
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virtual
SGVector<float64_t>
compute_squared_mmd
(
CKernel
* kernel,
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CList
* data,
index_t
num_this_run);
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private
:
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void
compute_squared_mmd
(
CKernel
* kernel,
CList
* data,
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SGVector<float64_t>
& current,
SGVector<float64_t>
& pp,
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SGVector<float64_t>
& qq,
SGVector<float64_t>
& pq,
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SGVector<float64_t>
& qp,
index_t
num_this_run);
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};
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}
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#endif
/* LINEAR_TIME_MMD_H_ */
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Machine Learning Toolbox - Documentation