svmclassification.h

强化学习算法（R-Learning）难得的珍贵资料

// Copyright (C) 2003 Ronan Collobert ([e-mail])
//                
// This file is part of Torch 3.
//
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// modification, are permitted provided that the following conditions
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#ifndef SVM_CLASSIFICATION_INC
#define SVM_CLASSIFICATION_INC

#include "SVM.h"

namespace Torch {


/** SVM in classification.

    Try to find the hyperplane $w.x+b = 0$
    as
    $(w,b)$ minimize $0.5*||w||^2 + \sum_j C_j |1- y_j*(w.x_j+b)|_+$

    (where $|x|_+ = x$ if $x > 0$, else $0$)

    (in fact, we use a #kernel# instead of a dot product)

    The $C_j$ coefficients are given in #C_# when you
    call the constructor. If this one is NULL, then
    the value given by the "C" option is used for
    all $C_j$.
    (The size of #C_# \emph{must be} #data->n_real_examples#)

    Options:
    \begin{tabular}{lcll}
      "C"          &  real &  trade off between the weight decay and the error & [100] \\
      "cache size" & real  &  cache size (in Mo)                               & [50]
    \end{tabular}

    @author Ronan Collobert ([e-mail])
*/
class SVMClassification : public SVM
{
  private:
    char *sequences_buffer;
    char *frames_buffer;

  public:
    real cache_size_in_megs;
    real *Cuser;
    real C_cst;

    //-----

    ///
    SVMClassification(Kernel *kernel_, real *C_=NULL, IOSequenceArray *io_sequence_array_=NULL);

    //-----

    virtual void setDataSet(DataSet *dataset_);
    virtual void checkSupportVectors();
    virtual ~SVMClassification();
};

}

#endif