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// Copyright (C) 2003--2004 Ronan Collobert (collober@idiap.ch)
//
// This file is part of Torch 3.1.
//
// 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.
// 3. The name of the author may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``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 AUTHOR 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.
#include "SVM.h"
#include "XFile.h"
namespace Torch {
SVM::SVM(Kernel *kernel_, IOSequenceArray *io_sequence_array_)
{
data = NULL;
kernel = kernel_;
support_vectors = NULL;
n_support_vectors = 0;
n_support_vectors_bound = 0;
sv_alpha = NULL;
sv_sequences = NULL;
sv_allocator = new Allocator;
outputs = new(allocator) Sequence(1, 1);
if(io_sequence_array_)
io_sequence_array = io_sequence_array_;
else
io_sequence_array = new(allocator) IOSequenceArray;
}
void SVM::forward(Sequence *inputs)
{
real sum = 0;
for(int t = 0; t < n_support_vectors; t++)
sum += sv_alpha[t]*kernel->eval(sv_sequences[t], inputs);
sum += b;
outputs->frames[0][0] = sum;
}
bool SVM::bCompute()
{
real sum = 0;
int n_ = 0;
for(int it = 0; it < n_support_vectors; it++)
{
int t = support_vectors[it];
if( (alpha[t] > Cdown[t]+bound_eps) && (alpha[t] < Cup[t]-bound_eps) )
{
sum += y[t]*grad[t];
n_++;
}
}
if(n_)
{
b = -sum/(real)n_;
return(true);
}
else
return(false);
}
void SVM::loadXFile(XFile *file)
{
file->taggedRead(&b, sizeof(real), 1, "b");
file->taggedRead(&n_support_vectors, sizeof(int), 1, "NSV");
file->taggedRead(&n_support_vectors_bound, sizeof(int), 1, "NSVB");
sv_allocator->freeAll();
if(n_support_vectors > 0)
{
sv_alpha = (real *)sv_allocator->alloc(sizeof(real)*n_support_vectors);
file->taggedRead(sv_alpha, sizeof(real), n_support_vectors, "SVALPHA");
sv_sequences = (Sequence **)sv_allocator->alloc(sizeof(Sequence *)*n_support_vectors);
io_sequence_array->read(file, sv_sequences, n_support_vectors, sv_allocator);
}
else
{
sv_alpha = NULL;
sv_sequences = NULL;
}
}
void SVM::saveXFile(XFile *file)
{
file->taggedWrite(&b, sizeof(real), 1, "b");
file->taggedWrite(&n_support_vectors, sizeof(int), 1, "NSV");
file->taggedWrite(&n_support_vectors_bound, sizeof(int), 1, "NSVB");
if(n_support_vectors > 0)
{
file->taggedWrite(sv_alpha, sizeof(real), n_support_vectors, "SVALPHA");
io_sequence_array->write(file, sv_sequences, n_support_vectors);
}
}
SVM::~SVM()
{
delete sv_allocator;
}
}
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