SHOGUN
v1.1.0
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Multiple Kernel Learning for one-class-classification.
Learns a One-Class SVM classifier and its kernel weights. Makes only sense if multiple kernels are used.
Definition at line 25 of file MKLOneClass.h.
Protected Member Functions | |
virtual void | init_training () |
virtual EClassifierType | get_classifier_type () |
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virtual bool | train_machine (CFeatures *data=NULL) |
void | perform_mkl_step (float64_t *beta, float64_t *old_beta, int num_kernels, int32_t *label, int32_t *active2dnum, float64_t *a, float64_t *lin, float64_t *sumw, int32_t &inner_iters) |
float64_t | compute_optimal_betas_via_cplex (float64_t *beta, const float64_t *old_beta, int32_t num_kernels, const float64_t *sumw, float64_t suma, int32_t &inner_iters) |
float64_t | compute_optimal_betas_via_glpk (float64_t *beta, const float64_t *old_beta, int num_kernels, const float64_t *sumw, float64_t suma, int32_t &inner_iters) |
float64_t | compute_optimal_betas_elasticnet (float64_t *beta, const float64_t *old_beta, const int32_t num_kernels, const float64_t *sumw, const float64_t suma, const float64_t mkl_objective) |
void | elasticnet_transform (float64_t *beta, float64_t lmd, int32_t len) |
void | elasticnet_dual (float64_t *ff, float64_t *gg, float64_t *hh, const float64_t &del, const float64_t *nm, int32_t len, const float64_t &lambda) |
float64_t | compute_optimal_betas_directly (float64_t *beta, const float64_t *old_beta, const int32_t num_kernels, const float64_t *sumw, const float64_t suma, const float64_t mkl_objective) |
float64_t | compute_optimal_betas_block_norm (float64_t *beta, const float64_t *old_beta, const int32_t num_kernels, const float64_t *sumw, const float64_t suma, const float64_t mkl_objective) |
float64_t | compute_optimal_betas_newton (float64_t *beta, const float64_t *old_beta, int32_t num_kernels, const float64_t *sumw, float64_t suma, float64_t mkl_objective) |
virtual bool | converged () |
void | init_solver () |
bool | init_cplex () |
void | set_qnorm_constraints (float64_t *beta, int32_t num_kernels) |
bool | cleanup_cplex () |
bool | init_glpk () |
bool | cleanup_glpk () |
bool | check_lpx_status (LPX *lp) |
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virtual float64_t * | get_linear_term_array () |
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virtual void | store_model_features () |
Additional Inherited Members | |
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static bool | perform_mkl_step_helper (CMKL *mkl, const float64_t *sumw, const float64_t suma) |
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SGIO * | io |
Parallel * | parallel |
Version * | version |
Parameter * | m_parameters |
Parameter * | m_model_selection_parameters |
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CSVM * | svm |
float64_t | C_mkl |
float64_t | mkl_norm |
float64_t | ent_lambda |
float64_t | mkl_block_norm |
float64_t * | beta_local |
int32_t | mkl_iterations |
float64_t | mkl_epsilon |
bool | interleaved_optimization |
float64_t * | W |
float64_t | w_gap |
float64_t | rho |
CTime | training_time_clock |
CPXENVptr | env |
CPXLPptr | lp_cplex |
LPX * | lp_glpk |
bool | lp_initialized |
CMKLOneClass | ( | CSVM * | s = NULL | ) |
Constructor
s | SVM to use as constraint generator in MKL SILP |
Definition at line 6 of file MKLOneClass.cpp.
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virtual |
Destructor
Definition at line 12 of file MKLOneClass.cpp.
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virtual |
compute beta independent term from objective, e.g., in 2-class MKL sum_i alpha_i etc
Implements CMKL.
Definition at line 16 of file MKLOneClass.cpp.
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protectedvirtual |
get classifier type
Reimplemented from CMachine.
Definition at line 53 of file MKLOneClass.h.
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protectedvirtual |
check run before starting training (to e.g. check if labeling is two-class labeling in classification case
Implements CMKL.
Definition at line 21 of file MKLOneClass.cpp.