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src
shogun
loss
HingeLoss.cpp
Go to the documentation of this file.
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/*
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Copyright (c) 2009 Yahoo! Inc. All rights reserved. The copyrights
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embodied in the content of this file are licensed under the BSD
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(revised) open source license.
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Copyright (c) 2011 Berlin Institute of Technology and Max-Planck-Society.
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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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Modifications (w) 2011 Shashwat Lal Das
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Modifications (w) 2012 Fernando José Iglesias García
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*/
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#include <
shogun/loss/HingeLoss.h
>
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#include <
shogun/mathematics/Math.h
>
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using namespace
shogun;
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float64_t
CHingeLoss::loss
(
float64_t
prediction,
float64_t
label)
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{
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float64_t
e = 1 - label * prediction;
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return
(e > 0) ? e : 0;
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}
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float64_t
CHingeLoss::loss
(
float64_t
z)
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{
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return
CMath::max
(0.0, z);
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}
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float64_t
CHingeLoss::first_derivative
(
float64_t
prediction,
float64_t
label)
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{
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return
(label * prediction >= label * label) ? 0 : -label;
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}
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float64_t
CHingeLoss::first_derivative
(
float64_t
z)
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{
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return
z > 0.0 ? 1.0 : 0.0;
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}
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float64_t
CHingeLoss::second_derivative
(
float64_t
prediction,
float64_t
label)
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{
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return
0.;
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}
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float64_t
CHingeLoss::second_derivative
(
float64_t
z)
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{
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return
0;
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}
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float64_t
CHingeLoss::get_update
(
float64_t
prediction,
float64_t
label,
float64_t
eta_t,
float64_t
norm
)
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{
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if
(label * prediction >= label * label)
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return
0;
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float64_t
err = (label*label - label*prediction)/(label * label);
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float64_t
normal = eta_t;
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return
label * (normal < err ? normal : err)/norm;
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}
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float64_t
CHingeLoss::get_square_grad
(
float64_t
prediction,
float64_t
label)
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{
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return
first_derivative
(prediction, label);
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}
SHOGUN
Machine Learning Toolbox - Documentation