Point Cloud Library (PCL) 1.12.0
svm.h
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38
39#pragma once
40
41#define LIBSVM_VERSION 311
42
43#ifdef __cplusplus
44extern "C" {
45#endif
46
47extern int libsvm_version;
48
49struct svm_node {
50 int index;
51 double value;
52};
53
55 int l;
56 double* y;
57
58 struct svm_node** x;
59};
60
62 // index = 1 if usable, index = 0 if not
63
64 struct svm_node* obj;
65
66 // max features scaled
67 int max;
68
69 svm_scaling() : max(0) {}
70};
71
72enum { C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, NU_SVR }; /* svm_type */
73enum { LINEAR, POLY, RBF, SIGMOID, PRECOMPUTED }; /* kernel_type */
74
78 int degree; /* for poly */
79 double gamma; /* for poly/rbf/sigmoid */
80 double coef0; /* for poly/sigmoid */
81
82 /* these are for training only */
83 double cache_size; /* in MB */
84 double eps; /* stopping criteria */
85 double C; /* for C_SVC, EPSILON_SVR and NU_SVR */
86 int nr_weight; /* for C_SVC */
87 int* weight_label; /* for C_SVC */
88 double* weight; /* for C_SVC */
89 double nu; /* for NU_SVC, ONE_CLASS, and NU_SVR */
90 double p; /* for EPSILON_SVR */
91 int shrinking; /* use the shrinking heuristics */
92 int probability; /* do probability estimates */
93};
94
95//
96// svm_model
97//
98
99struct svm_model {
100
101 struct svm_parameter param; /* parameter */
102 int nr_class; /* number of classes, = 2 in regression/one class svm */
103 int l; /* total #SV */
104
105 struct svm_node** SV; /* SVs (SV[l]) */
106 double** sv_coef; /* coefficients for SVs in decision functions (sv_coef[k-1][l]) */
107 double* rho; /* constants in decision functions (rho[k*(k-1)/2]) */
108 double* probA; /* pariwise probability information */
109 double* probB;
110
111 /* for classification only */
112
113 int* label; /* label of each class (label[k]) */
114 int* nSV; /* number of SVs for each class (nSV[k]) */
115 /* nSV[0] + nSV[1] + ... + nSV[k-1] = l */
116 /* XXX */
117 int free_sv; /* 1 if svm_model is created by svm_load_model*/
118 /* 0 if svm_model is created by svm_train */
119
120 /* for scaling */
121
123};
124
125struct svm_model*
126svm_train(const struct svm_problem* prob, const struct svm_parameter* param);
127void
128svm_cross_validation(const struct svm_problem* prob,
129 const struct svm_parameter* param,
130 int nr_fold,
131 double* target);
132
133int
134svm_save_model(const char* model_file_name, const struct svm_model* model);
135
136struct svm_model*
137svm_load_model(const char* model_file_name);
138
139int
140svm_get_svm_type(const struct svm_model* model);
141
142int
143svm_get_nr_class(const struct svm_model* model);
144
145void
146svm_get_labels(const struct svm_model* model, int* label);
147
148double
149svm_get_svr_probability(const struct svm_model* model);
150
151double
152svm_predict_values(const struct svm_model* model,
153 const struct svm_node* x,
154 double* dec_values);
155double
156svm_predict(const struct svm_model* model, const struct svm_node* x);
157
158double
159svm_predict_probability(const struct svm_model* model,
160 const struct svm_node* x,
161 double* prob_estimates);
162
163void
164svm_free_model_content(struct svm_model* model_ptr);
165
166void
167svm_free_and_destroy_model(struct svm_model** model_ptr_ptr);
168
169void
170svm_destroy_param(struct svm_parameter* param);
171
172const char*
173svm_check_parameter(const struct svm_problem* prob, const struct svm_parameter* param);
174
175int
176svm_check_probability_model(const struct svm_model* model);
177
178void
179svm_set_print_string_function(void (*print_func)(const char*));
180
181#ifdef __cplusplus
182}
183
184#endif
Definition: svm.h:99
double * rho
Definition: svm.h:107
int * nSV
Definition: svm.h:114
int free_sv
Definition: svm.h:117
int nr_class
Definition: svm.h:102
struct svm_node * scaling
Definition: svm.h:122
double * probB
Definition: svm.h:109
struct svm_parameter param
Definition: svm.h:101
struct svm_node ** SV
Definition: svm.h:105
double ** sv_coef
Definition: svm.h:106
int l
Definition: svm.h:103
int * label
Definition: svm.h:113
double * probA
Definition: svm.h:108
Definition: svm.h:49
double value
Definition: svm.h:51
int index
Definition: svm.h:50
double cache_size
Definition: svm.h:83
int * weight_label
Definition: svm.h:87
double eps
Definition: svm.h:84
double coef0
Definition: svm.h:80
int svm_type
Definition: svm.h:76
double p
Definition: svm.h:90
int kernel_type
Definition: svm.h:77
int nr_weight
Definition: svm.h:86
double nu
Definition: svm.h:89
double gamma
Definition: svm.h:79
double C
Definition: svm.h:85
int probability
Definition: svm.h:92
int shrinking
Definition: svm.h:91
int degree
Definition: svm.h:78
double * weight
Definition: svm.h:88
int l
Definition: svm.h:55
double * y
Definition: svm.h:56
struct svm_node ** x
Definition: svm.h:58
struct svm_node * obj
Definition: svm.h:64
int max
Definition: svm.h:67
svm_scaling()
Definition: svm.h:69