Program Listing for File svm.h

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#ifndef _LIBSVM_H_
#define _LIBSVM_H_

#define LIBSVM_VERSION 311

#ifdef __cplusplus
extern "C"
{
#endif

  extern int libsvm_version;

  struct svm_node
  {
    int index;
    double value;
  };

  struct svm_problem
  {
    int l;
    double *y;

    struct svm_node **x;
  };

  struct svm_scaling
  {
    // index = 1 if usable, index = 0 if not

    struct svm_node *obj;

    // max features scaled
    int max;

    svm_scaling() : max(0)
    {
    }
  };

  enum { C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, NU_SVR }; /* svm_type */
  enum { LINEAR, POLY, RBF, SIGMOID, PRECOMPUTED }; /* kernel_type */

  struct svm_parameter
  {
    int svm_type;
    int kernel_type;
    int degree; /* for poly */
    double gamma; /* for poly/rbf/sigmoid */
    double coef0; /* for poly/sigmoid */

    /* these are for training only */
    double cache_size; /* in MB */
    double eps; /* stopping criteria */
    double C; /* for C_SVC, EPSILON_SVR and NU_SVR */
    int nr_weight;  /* for C_SVC */
    int *weight_label; /* for C_SVC */
    double* weight;  /* for C_SVC */
    double nu; /* for NU_SVC, ONE_CLASS, and NU_SVR */
    double p; /* for EPSILON_SVR */
    int shrinking; /* use the shrinking heuristics */
    int probability; /* do probability estimates */
  };

//
// svm_model
//

  struct svm_model
  {

    struct svm_parameter param; /* parameter */
    int nr_class;  /* number of classes, = 2 in regression/one class svm */
    int l;   /* total #SV */

    struct svm_node **SV;  /* SVs (SV[l]) */
    double **sv_coef; /* coefficients for SVs in decision functions (sv_coef[k-1][l]) */
    double *rho;  /* constants in decision functions (rho[k*(k-1)/2]) */
    double *probA;  /* pariwise probability information */
    double *probB;

    /* for classification only */

    int *label;  /* label of each class (label[k]) */
    int *nSV;  /* number of SVs for each class (nSV[k]) */
    /* nSV[0] + nSV[1] + ... + nSV[k-1] = l */
    /* XXX */
    int free_sv;  /* 1 if svm_model is created by svm_load_model*/
    /* 0 if svm_model is created by svm_train */

    /* for scaling */

    struct svm_node *scaling;
  };

  struct svm_model *svm_train (const struct svm_problem *prob, const struct svm_parameter *param);
  void svm_cross_validation (const struct svm_problem *prob, const struct svm_parameter *param, int nr_fold, double *target);

  int svm_save_model (const char *model_file_name, const struct svm_model *model);

  struct svm_model *svm_load_model (const char *model_file_name);

  int svm_get_svm_type (const struct svm_model *model);
  int svm_get_nr_class (const struct svm_model *model);
  void svm_get_labels (const struct svm_model *model, int *label);
  double svm_get_svr_probability (const struct svm_model *model);

  double svm_predict_values (const struct svm_model *model, const struct svm_node *x, double* dec_values);
  double svm_predict (const struct svm_model *model, const struct svm_node *x);
  double svm_predict_probability (const struct svm_model *model, const struct svm_node *x, double* prob_estimates);

  void svm_free_model_content (struct svm_model *model_ptr);
  void svm_free_and_destroy_model (struct svm_model **model_ptr_ptr);
  void svm_destroy_param (struct svm_parameter *param);

  const char *svm_check_parameter (const struct svm_problem *prob, const struct svm_parameter *param);
  int svm_check_probability_model (const struct svm_model *model);

  void svm_set_print_string_function (void (*print_func) (const char *));

#ifdef __cplusplus
}

#endif

#endif /* _LIBSVM_H_ */