11 #ifndef _GUICLASSIFIER_H__
12 #define _GUICLASSIFIER_H__
41 bool load(
char* filename,
char* type);
45 bool save(
char* param);
74 float64_t* &weights, int32_t& rows, int32_t& cols,
75 float64_t*& bias, int32_t& brows, int32_t& bcols,
90 float64_t* &weights, int32_t& rows, int32_t& cols,
91 float64_t*& bias, int32_t& brows, int32_t& bcols,
102 float64_t* &weights, int32_t& rows, int32_t& cols,
103 float64_t*& bias, int32_t& brows, int32_t& bcols);
113 float64_t* &weights, int32_t& rows, int32_t& cols,
114 float64_t*& bias, int32_t& brows, int32_t& bcols);
226 virtual const char*
get_name()
const {
return "GUIClassifier"; }
bool set_perceptron_parameters(float64_t lernrate, int32_t maxiter)
bool set_svm_epsilon(float64_t epsilon)
bool get_trained_classifier(float64_t *&weights, int32_t &rows, int32_t &cols, float64_t *&bias, int32_t &brows, int32_t &bcols, int32_t idx=-1)
CLabels * classify_linear()
bool set_svm_shrinking_enabled(bool enabled)
bool train_mkl_multiclass()
bool set_svm_linadd_enabled(bool enabled)
bool train_knn(int32_t k=3)
bool set_constraint_generator(char *cg)
bool train_clustering(int32_t k=3, int32_t max_iter=1000)
The class Labels models labels, i.e. class assignments of objects.
bool set_svm_mkl_parameters(float64_t weight_epsilon, float64_t C_mkl, float64_t mkl_norm)
float64_t perceptron_learnrate
bool set_do_auc_maximization(bool do_auc)
bool set_svm_nu(float64_t nu)
int32_t perceptron_maxiter
bool svm_use_precompute_subkernel
bool svm_use_precompute_subkernel_light
bool train_sparse_linear()
A generic learning machine interface.
bool classify_example(int32_t idx, float64_t &result)
bool set_svm_batch_computation_enabled(bool enabled)
CLabels * classify_distancemachine()
static const float64_t epsilon
CLabels * classify_kernelmachine()
bool new_classifier(char *name, int32_t d=6, int32_t from_d=40)
bool set_svr_tube_epsilon(float64_t tube_epsilon)
Class SGObject is the base class of all shogun objects.
bool set_svm_max_qpsize(int32_t max_qpsize)
bool set_solver(char *solver)
float64_t svm_weight_epsilon
bool set_mkl_block_norm(float64_t mkl_bnorm)
bool set_mkl_interleaved_enabled(bool enabled)
CMachine * get_classifier()
bool set_svm_bufsize(int32_t bufsize)
bool set_svm_bias_enabled(bool enabled)
bool set_svm_precompute_enabled(int32_t precompute)
bool get_clustering(float64_t *&weights, int32_t &rows, int32_t &cols, float64_t *&bias, int32_t &brows, int32_t &bcols)
bool get_svm(float64_t *&weights, int32_t &rows, int32_t &cols, float64_t *&bias, int32_t &brows, int32_t &bcols, int32_t idx=-1)
bool get_linear(float64_t *&weights, int32_t &rows, int32_t &cols, float64_t *&bias, int32_t &brows, int32_t &bcols)
bool train_linear(float64_t gamma=0)
CSVM * constraint_generator
all of classes and functions are contained in the shogun namespace
bool svm_do_auc_maximization
A generic Support Vector Machine Interface.
CLabels * classify_byte_linear()
Matrix::Scalar max(Matrix m)
virtual const char * get_name() const
float64_t svm_tube_epsilon
bool set_krr_tau(float64_t tau=1)
bool set_svm_C(float64_t C1, float64_t C2)
bool load(char *filename, char *type)
bool set_elasticnet_lambda(float64_t lambda)
bool svm_use_batch_computation
bool set_svm_qpsize(int32_t qpsize)
bool set_max_train_time(float64_t max)