106 lines
3.4 KiB
C
106 lines
3.4 KiB
C
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#ifndef _LIBSVM_H
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#define _LIBSVM_H
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#define LIBSVM_VERSION 320
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#ifdef __cplusplus
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extern "C" {
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#endif
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extern int libsvm_version;
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struct svm_node
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{
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int index;
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double value;
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};
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struct svm_problem
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{
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int l;
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double *y;
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struct svm_node **x;
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double *W; /* instance weight */
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};
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enum { C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, NU_SVR }; /* svm_type */
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enum { LINEAR, POLY, RBF, SIGMOID, PRECOMPUTED }; /* kernel_type */
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struct svm_parameter
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{
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int svm_type;
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int kernel_type;
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int degree; /* for poly */
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double gamma; /* for poly/rbf/sigmoid */
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double coef0; /* for poly/sigmoid */
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/* these are for training only */
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double cache_size; /* in MB */
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double eps; /* stopping criteria */
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double C; /* for C_SVC, EPSILON_SVR and NU_SVR */
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int nr_weight; /* for C_SVC */
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int *weight_label; /* for C_SVC */
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double* weight; /* for C_SVC */
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double nu; /* for NU_SVC, ONE_CLASS, and NU_SVR */
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double p; /* for EPSILON_SVR */
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int shrinking; /* use the shrinking heuristics */
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int probability; /* do probability estimates */
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};
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//
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// svm_model
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//
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struct svm_model
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{
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struct svm_parameter param; /* parameter */
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int nr_class; /* number of classes, = 2 in regression/one class svm */
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int l; /* total #SV */
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struct svm_node **SV; /* SVs (SV[l]) */
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double **sv_coef; /* coefficients for SVs in decision functions (sv_coef[k-1][l]) */
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double *rho; /* constants in decision functions (rho[k*(k-1)/2]) */
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double *probA; /* pariwise probability information */
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double *probB;
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int *sv_indices; /* sv_indices[0,...,nSV-1] are values in [1,...,num_traning_data] to indicate SVs in the training set */
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/* for classification only */
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int *label; /* label of each class (label[k]) */
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int *nSV; /* number of SVs for each class (nSV[k]) */
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/* nSV[0] + nSV[1] + ... + nSV[k-1] = l */
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/* XXX */
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int free_sv; /* 1 if svm_model is created by svm_load_model*/
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/* 0 if svm_model is created by svm_train */
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};
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struct svm_model *svm_train(const struct svm_problem *prob, const struct svm_parameter *param);
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void svm_cross_validation(const struct svm_problem *prob, const struct svm_parameter *param, int nr_fold, double *target);
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int svm_save_model(const char *model_file_name, const struct svm_model *model);
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struct svm_model *svm_load_model(const char *model_file_name);
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int svm_get_svm_type(const struct svm_model *model);
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int svm_get_nr_class(const struct svm_model *model);
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void svm_get_labels(const struct svm_model *model, int *label);
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void svm_get_sv_indices(const struct svm_model *model, int *sv_indices);
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int svm_get_nr_sv(const struct svm_model *model);
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double svm_get_svr_probability(const struct svm_model *model);
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double svm_predict_values(const struct svm_model *model, const struct svm_node *x, double* dec_values);
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double svm_predict(const struct svm_model *model, const struct svm_node *x);
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double svm_predict_probability(const struct svm_model *model, const struct svm_node *x, double* prob_estimates);
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void svm_free_model_content(struct svm_model *model_ptr);
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void svm_free_and_destroy_model(struct svm_model **model_ptr_ptr);
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void svm_destroy_param(struct svm_parameter *param);
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const char *svm_check_parameter(const struct svm_problem *prob, const struct svm_parameter *param);
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int svm_check_probability_model(const struct svm_model *model);
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void svm_set_print_string_function(void (*print_func)(const char *));
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#ifdef __cplusplus
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}
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#endif
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#endif /* _LIBSVM_H */
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