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src
shogun
classifier
vw
vw_math.h
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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*
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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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* Adaptation of Vowpal Wabbit v5.1.
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* Copyright (C) 2011 Berlin Institute of Technology and Max-Planck-Society.
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*/
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#ifndef _VW_MATH_H__
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#define _VW_MATH_H__
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#include <
shogun/lib/common.h
>
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#include <
shogun/mathematics/Math.h
>
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#include <
shogun/classifier/vw/vw_common.h
>
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namespace
shogun
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{
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inline
float32_t
real_weight
(
float32_t
w,
float32_t
gravity)
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{
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float32_t
wprime = 0.;
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if
(gravity < fabsf(w))
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wprime =
CMath::sign
(w)*(fabsf(w) - gravity);
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return
wprime;
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}
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float32_t
sd_offset_add
(
float32_t
* weights,
vw_size_t
mask, VwFeature* begin,
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VwFeature* end,
vw_size_t
offset);
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float32_t
sd_offset_truncadd
(
float32_t
* weights,
vw_size_t
mask, VwFeature* begin,
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VwFeature* end,
vw_size_t
offset,
float32_t
gravity);
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float32_t
one_pf_quad_predict
(
float32_t
* weights, VwFeature& f,
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v_array<VwFeature> &cross_features,
vw_size_t
mask);
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float32_t
one_pf_quad_predict_trunc
(
float32_t
* weights, VwFeature& f,
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v_array<VwFeature> &cross_features,
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vw_size_t
mask,
float32_t
gravity);
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}
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#endif // _VW_MATH_H__
SHOGUN
Machine Learning Toolbox - Documentation