/usr/include/torch/SVMRegression.h is in libtorch3-dev 3.1-2.2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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//
// This file is part of Torch 3.1.
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#ifndef SVM_REGRESSION_INC
#define SVM_REGRESSION_INC
#include "SVM.h"
namespace Torch {
/** SVM in regression.
Try to find the hyperplane f(x) = w.x+b
as
$(w,b)$ minimize $0.5*||w||^2 + \sum_j C_j |w.x_j+b -y_j -eps|_+$
$+ \sum_j C_(j+n) |y_j -w.x_j-b -eps|_+$
(where $|x|_+ = x$ if $x > 0$, else $0$)
(and $n$ is the number of training examples)
(the size of $C$ is here 2*$n$)
("eps" is #eps_regression# in the code)
(in fact, we use a kernel #kernel# instead of
a dot product)
The $C_j$ coefficients are given by #C_# when you
call the constructor. If this one is NULL, all
#C_j# will have the value given by the "C" option.
(The size of #C_# \emph{must be} #2*data->n_real_examples#)
Options:
\begin{tabular}{lcll}
"C" & real & trade off between the weight decay and the error & [100] \\
"eps regression" & real & size of the error tube & [0.7] \\
"cache size" & real & cache size (in Mo) & [50]
\end{tabular}
@author Ronan Collobert (collober@idiap.ch)
*/
class SVMRegression : public SVM
{
private:
char *sequences_buffer;
char *frames_buffer;
public:
real cache_size_in_megs;
real eps_regression;
real *Cuser;
real C_cst;
//-----
///
SVMRegression(Kernel *kernel_, real *C_=NULL, IOSequenceArray *io_sequence_array_=NULL);
//-----
virtual void setDataSet(DataSet *dataset_);
virtual void checkSupportVectors();
virtual ~SVMRegression();
};
}
#endif
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