* @brief params for ThunderSVM */
| 11 | * @brief params for ThunderSVM |
| 12 | */ |
| 13 | struct SvmParam { |
| 14 | SvmParam() { |
| 15 | svm_type = C_SVC; |
| 16 | kernel_type = RBF; |
| 17 | C = 1; |
| 18 | gamma = 0; |
| 19 | p = 0.1f; |
| 20 | epsilon = 0.001f; |
| 21 | nu = 0.5; |
| 22 | probability = false; |
| 23 | nr_weight = 0; |
| 24 | degree = 3; |
| 25 | coef0 = 0; |
| 26 | max_mem_size = static_cast<size_t>(8192) << 20; |
| 27 | } |
| 28 | |
| 29 | /// SVM type |
| 30 | enum SVM_TYPE { |
| 31 | C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, NU_SVR |
| 32 | }; |
| 33 | /// kernel function type |
| 34 | enum KERNEL_TYPE { |
| 35 | LINEAR, POLY, RBF, SIGMOID, PRECOMPUTED |
| 36 | }; |
| 37 | SVM_TYPE svm_type; |
| 38 | KERNEL_TYPE kernel_type; |
| 39 | |
| 40 | ///regularization parameter |
| 41 | float_type C; |
| 42 | ///for RBF kernel |
| 43 | float_type gamma; |
| 44 | ///for regression |
| 45 | float_type p; |
| 46 | ///for \f$\nu\f$-SVM |
| 47 | float_type nu; |
| 48 | ///stopping criteria |
| 49 | float_type epsilon; |
| 50 | ///degree for polynomial kernel |
| 51 | int degree; |
| 52 | ///for polynomial/sigmoid kernel |
| 53 | float_type coef0; |
| 54 | ///for SVC |
| 55 | int nr_weight; |
| 56 | ///for SVC |
| 57 | int *weight_label; |
| 58 | ///for SVC |
| 59 | float_type *weight; |
| 60 | ///do probability estimates |
| 61 | int probability; |
| 62 | ///maximum memory size |
| 63 | size_t max_mem_size; |
| 64 | static const char *kernel_type_name[6]; |
| 65 | static const char *svm_type_name[6]; |
| 66 | }; |
| 67 | #endif //THUNDERSVM_SVMPARAM_H |