|
SHOGUN
4.1.0
|
Class SVRLight, performs support vector regression using SVMLight.
The SVR solution can be expressed as
\[ f({\bf x})=\sum_{i=1}^{N} \alpha_i k({\bf x}, {\bf x_i})+b \]
where \(\alpha\) and \(b\) are determined in training, i.e. using a pre-specified kernel, a given tube-epsilon for the epsilon insensitive loss, the follwoing quadratic problem is minimized (using the chunking decomposition technique)
\begin{eqnarray*} \max_{{\bf \alpha},{\bf \alpha}^*} &-\frac{1}{2}\sum_{i,j=1}^N(\alpha_i-\alpha_i^*)(\alpha_j-\alpha_j^*){\bf x}_i^T {\bf x}_j -\sum_{i=1}^N(\alpha_i+\alpha_i^*)\epsilon - \sum_{i=1}^N(\alpha_i-\alpha_i^*)y_i\\ \mbox{wrt}:& {\bf \alpha},{\bf \alpha}^*\in{\bf R}^N\\ \mbox{s.t.}:& 0\leq \alpha_i,\alpha_i^*\leq C,\, \forall i=1\dots N\\ &\sum_{i=1}^N(\alpha_i-\alpha_i^*)y_i=0 \end{eqnarray*}
Note that the SV regression problem is reduced to the standard SV classification problem by introducing artificial labels \(-y_i\) which leads to the epsilon insensitive loss constraints *
\begin{eqnarray*} {\bf w}^T{\bf x}_i+b-c_i-\xi_i\leq 0,&\, \forall i=1\dots N\\ -{\bf w}^T{\bf x}_i-b-c_i^*-\xi_i^*\leq 0,&\, \forall i=1\dots N \end{eqnarray*}
with \(c_i=y_i+ \epsilon\) and \(c_i^*=-y_i+ \epsilon\)
This implementation supports multiple kernel learning, i.e. if a CCombinedKernel is used the weights \(\beta\) in \( k_{combined}({\bf x}, {\bf x'}) = \sum_{m=0}^M \beta_m k_m({\bf x}, {\bf x'})\) can be determined in training (cf. Large Scale Multiple Kernel Learning Sonnenburg, Raetsch, Schaefer, Schoelkopf 2006).
linadd optimizations were implemented for kernels that support it (most string kernels and the linear kernel), which will result in significant speedups.
在文件 SVRLight.h 第 62 行定义.
Public 成员函数 | |
| MACHINE_PROBLEM_TYPE (PT_REGRESSION) | |
| CSVRLight () | |
| CSVRLight (float64_t C, float64_t epsilon, CKernel *k, CLabels *lab) | |
| virtual | ~CSVRLight () |
| virtual EMachineType | get_classifier_type () |
| void | svr_learn () |
| virtual float64_t | compute_objective_function (float64_t *a, float64_t *lin, float64_t *c, float64_t *eps, int32_t *label, int32_t totdoc) |
| virtual void | update_linear_component (int32_t *docs, int32_t *label, int32_t *active2dnum, float64_t *a, float64_t *a_old, int32_t *working2dnum, int32_t totdoc, float64_t *lin, float64_t *aicache, float64_t *c) |
| virtual void | update_linear_component_mkl (int32_t *docs, int32_t *label, int32_t *active2dnum, float64_t *a, float64_t *a_old, int32_t *working2dnum, int32_t totdoc, float64_t *lin, float64_t *aicache, float64_t *c) |
| virtual void | update_linear_component_mkl_linadd (int32_t *docs, int32_t *label, int32_t *active2dnum, float64_t *a, float64_t *a_old, int32_t *working2dnum, int32_t totdoc, float64_t *lin, float64_t *aicache, float64_t *c) |
| void | call_mkl_callback (float64_t *a, int32_t *label, float64_t *lin, float64_t *c, int32_t totdoc) |
| virtual void | reactivate_inactive_examples (int32_t *label, float64_t *a, SHRINK_STATE *shrink_state, float64_t *lin, float64_t *c, int32_t totdoc, int32_t iteration, int32_t *inconsistent, int32_t *docs, float64_t *aicache, float64_t *maxdiff) |
| virtual const char * | get_name () const |
| void | init () |
| int32_t | get_runtime () |
| void | svm_learn () |
| int32_t | optimize_to_convergence (int32_t *docs, int32_t *label, int32_t totdoc, SHRINK_STATE *shrink_state, int32_t *inconsistent, float64_t *a, float64_t *lin, float64_t *c, TIMING *timing_profile, float64_t *maxdiff, int32_t heldout, int32_t retrain) |
| void | clear_index (int32_t *index) |
| void | add_to_index (int32_t *index, int32_t elem) |
| int32_t | compute_index (int32_t *binfeature, int32_t range, int32_t *index) |
| void | optimize_svm (int32_t *docs, int32_t *label, int32_t *exclude_from_eq_const, float64_t eq_target, int32_t *chosen, int32_t *active2dnum, int32_t totdoc, int32_t *working2dnum, int32_t varnum, float64_t *a, float64_t *lin, float64_t *c, float64_t *aicache, QP *qp, float64_t *epsilon_crit_target) |
| void | compute_matrices_for_optimization (int32_t *docs, int32_t *label, int32_t *exclude_from_eq_const, float64_t eq_target, int32_t *chosen, int32_t *active2dnum, int32_t *key, float64_t *a, float64_t *lin, float64_t *c, int32_t varnum, int32_t totdoc, float64_t *aicache, QP *qp) |
| void | compute_matrices_for_optimization_parallel (int32_t *docs, int32_t *label, int32_t *exclude_from_eq_const, float64_t eq_target, int32_t *chosen, int32_t *active2dnum, int32_t *key, float64_t *a, float64_t *lin, float64_t *c, int32_t varnum, int32_t totdoc, float64_t *aicache, QP *qp) |
| int32_t | calculate_svm_model (int32_t *docs, int32_t *label, float64_t *lin, float64_t *a, float64_t *a_old, float64_t *c, int32_t *working2dnum, int32_t *active2dnum) |
| int32_t | check_optimality (int32_t *label, float64_t *a, float64_t *lin, float64_t *c, int32_t totdoc, float64_t *maxdiff, float64_t epsilon_crit_org, int32_t *misclassified, int32_t *inconsistent, int32_t *active2dnum, int32_t *last_suboptimal_at, int32_t iteration) |
| void | update_linear_component_mkl (int32_t *docs, int32_t *label, int32_t *active2dnum, float64_t *a, float64_t *a_old, int32_t *working2dnum, int32_t totdoc, float64_t *lin, float64_t *aicache) |
| void | update_linear_component_mkl_linadd (int32_t *docs, int32_t *label, int32_t *active2dnum, float64_t *a, float64_t *a_old, int32_t *working2dnum, int32_t totdoc, float64_t *lin, float64_t *aicache) |
| void | call_mkl_callback (float64_t *a, int32_t *label, float64_t *lin) |
| int32_t | select_next_qp_subproblem_grad (int32_t *label, float64_t *a, float64_t *lin, float64_t *c, int32_t totdoc, int32_t qp_size, int32_t *inconsistent, int32_t *active2dnum, int32_t *working2dnum, float64_t *selcrit, int32_t *select, int32_t cache_only, int32_t *key, int32_t *chosen) |
| int32_t | select_next_qp_subproblem_rand (int32_t *label, float64_t *a, float64_t *lin, float64_t *c, int32_t totdoc, int32_t qp_size, int32_t *inconsistent, int32_t *active2dnum, int32_t *working2dnum, float64_t *selcrit, int32_t *select, int32_t *key, int32_t *chosen, int32_t iteration) |
| void | select_top_n (float64_t *selcrit, int32_t range, int32_t *select, int32_t n) |
| void | init_shrink_state (SHRINK_STATE *shrink_state, int32_t totdoc, int32_t maxhistory) |
| void | shrink_state_cleanup (SHRINK_STATE *shrink_state) |
| int32_t | shrink_problem (SHRINK_STATE *shrink_state, int32_t *active2dnum, int32_t *last_suboptimal_at, int32_t iteration, int32_t totdoc, int32_t minshrink, float64_t *a, int32_t *inconsistent, float64_t *c, float64_t *lin, int *label) |
| MACHINE_PROBLEM_TYPE (PT_BINARY) | |
| void | set_defaults (int32_t num_sv=0) |
| virtual SGVector< float64_t > | get_linear_term () |
| virtual void | set_linear_term (const SGVector< float64_t > linear_term) |
| bool | load (FILE *svm_file) |
| bool | save (FILE *svm_file) |
| void | set_nu (float64_t nue) |
| void | set_C (float64_t c_neg, float64_t c_pos) |
| void | set_epsilon (float64_t eps) |
| void | set_tube_epsilon (float64_t eps) |
| float64_t | get_tube_epsilon () |
| void | set_qpsize (int32_t qps) |
| float64_t | get_epsilon () |
| float64_t | get_nu () |
| float64_t | get_C1 () |
| float64_t | get_C2 () |
| int32_t | get_qpsize () |
| void | set_shrinking_enabled (bool enable) |
| bool | get_shrinking_enabled () |
| float64_t | compute_svm_dual_objective () |
| float64_t | compute_svm_primal_objective () |
| void | set_objective (float64_t v) |
| float64_t | get_objective () |
| void | set_callback_function (CMKL *m, bool(*cb)(CMKL *mkl, const float64_t *sumw, const float64_t suma)) |
| void | set_kernel (CKernel *k) |
| CKernel * | get_kernel () |
| void | set_batch_computation_enabled (bool enable) |
| bool | get_batch_computation_enabled () |
| void | set_linadd_enabled (bool enable) |
| bool | get_linadd_enabled () |
| void | set_bias_enabled (bool enable_bias) |
| bool | get_bias_enabled () |
| float64_t | get_bias () |
| void | set_bias (float64_t bias) |
| int32_t | get_support_vector (int32_t idx) |
| float64_t | get_alpha (int32_t idx) |
| bool | set_support_vector (int32_t idx, int32_t val) |
| bool | set_alpha (int32_t idx, float64_t val) |
| int32_t | get_num_support_vectors () |
| void | set_alphas (SGVector< float64_t > alphas) |
| void | set_support_vectors (SGVector< int32_t > svs) |
| SGVector< int32_t > | get_support_vectors () |
| SGVector< float64_t > | get_alphas () |
| bool | create_new_model (int32_t num) |
| bool | init_kernel_optimization () |
| virtual CRegressionLabels * | apply_regression (CFeatures *data=NULL) |
| virtual CBinaryLabels * | apply_binary (CFeatures *data=NULL) |
| virtual float64_t | apply_one (int32_t num) |
| virtual bool | train_locked (SGVector< index_t > indices) |
| virtual CBinaryLabels * | apply_locked_binary (SGVector< index_t > indices) |
| virtual CRegressionLabels * | apply_locked_regression (SGVector< index_t > indices) |
| virtual SGVector< float64_t > | apply_locked_get_output (SGVector< index_t > indices) |
| virtual void | data_lock (CLabels *labs, CFeatures *features=NULL) |
| virtual void | data_unlock () |
| virtual bool | supports_locking () const |
| virtual bool | train (CFeatures *data=NULL) |
| virtual CLabels * | apply (CFeatures *data=NULL) |
| virtual CMulticlassLabels * | apply_multiclass (CFeatures *data=NULL) |
| virtual CStructuredLabels * | apply_structured (CFeatures *data=NULL) |
| virtual CLatentLabels * | apply_latent (CFeatures *data=NULL) |
| virtual void | set_labels (CLabels *lab) |
| virtual CLabels * | get_labels () |
| void | set_max_train_time (float64_t t) |
| float64_t | get_max_train_time () |
| void | set_solver_type (ESolverType st) |
| ESolverType | get_solver_type () |
| virtual void | set_store_model_features (bool store_model) |
| virtual CLabels * | apply_locked (SGVector< index_t > indices) |
| virtual CMulticlassLabels * | apply_locked_multiclass (SGVector< index_t > indices) |
| virtual CStructuredLabels * | apply_locked_structured (SGVector< index_t > indices) |
| virtual CLatentLabels * | apply_locked_latent (SGVector< index_t > indices) |
| virtual void | post_lock (CLabels *labs, CFeatures *features) |
| bool | is_data_locked () const |
| virtual EProblemType | get_machine_problem_type () const |
| virtual CSGObject * | shallow_copy () const |
| virtual CSGObject * | deep_copy () const |
| virtual bool | is_generic (EPrimitiveType *generic) const |
| template<class T > | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| template<> | |
| void | set_generic () |
| void | unset_generic () |
| virtual void | print_serializable (const char *prefix="") |
| virtual bool | save_serializable (CSerializableFile *file, const char *prefix="") |
| virtual bool | load_serializable (CSerializableFile *file, const char *prefix="") |
| void | set_global_io (SGIO *io) |
| SGIO * | get_global_io () |
| void | set_global_parallel (Parallel *parallel) |
| Parallel * | get_global_parallel () |
| void | set_global_version (Version *version) |
| Version * | get_global_version () |
| SGStringList< char > | get_modelsel_names () |
| void | print_modsel_params () |
| char * | get_modsel_param_descr (const char *param_name) |
| index_t | get_modsel_param_index (const char *param_name) |
| void | build_gradient_parameter_dictionary (CMap< TParameter *, CSGObject * > *dict) |
| virtual void | update_parameter_hash () |
| virtual bool | parameter_hash_changed () |
| virtual bool | equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false) |
| virtual CSGObject * | clone () |
静态 Public 成员函数 | |
| static void * | update_linear_component_mkl_linadd_helper (void *p) |
| static void * | apply_helper (void *p) |
Public 属性 | |
| SGIO * | io |
| Parallel * | parallel |
| Version * | version |
| Parameter * | m_parameters |
| Parameter * | m_model_selection_parameters |
| Parameter * | m_gradient_parameters |
| uint32_t | m_hash |
Protected 成员函数 | |
| int32_t | regression_fix_index (int32_t i) |
| virtual float64_t | compute_kernel (int32_t i, int32_t j) |
| virtual bool | train_machine (CFeatures *data=NULL) |
| float64_t * | optimize_qp (QP *qp, float64_t *epsilon_crit, int32_t nx, float64_t *threshold, int32_t &svm_maxqpsize) |
| virtual float64_t * | get_linear_term_array () |
| SGVector< float64_t > | apply_get_outputs (CFeatures *data) |
| virtual void | store_model_features () |
| virtual bool | is_label_valid (CLabels *lab) const |
| virtual bool | train_require_labels () const |
| virtual void | load_serializable_pre () throw (ShogunException) |
| virtual void | load_serializable_post () throw (ShogunException) |
| virtual void | save_serializable_pre () throw (ShogunException) |
| virtual void | save_serializable_post () throw (ShogunException) |
静态 Protected 成员函数 | |
| static void * | update_linear_component_linadd_helper (void *params) |
| static int32_t | regression_fix_index2 (int32_t i, int32_t num_vectors) |
| static void * | compute_kernel_helper (void *p) |
| static void * | reactivate_inactive_examples_vanilla_helper (void *p) |
| static void * | reactivate_inactive_examples_linadd_helper (void *p) |
Protected 属性 | |
| int32_t | num_vectors |
| MODEL * | model |
| LEARN_PARM * | learn_parm |
| int32_t | verbosity |
| float64_t | init_margin |
| int32_t | init_iter |
| int32_t | precision_violations |
| float64_t | model_b |
| float64_t | opt_precision |
| float64_t * | primal |
| float64_t * | dual |
| float64_t * | W |
| int32_t | count |
| float64_t | mymaxdiff |
| bool | use_kernel_cache |
| bool | mkl_converged |
| SGVector< float64_t > | m_linear_term |
| bool | svm_loaded |
| float64_t | epsilon |
| float64_t | tube_epsilon |
| float64_t | nu |
| float64_t | C1 |
| float64_t | C2 |
| float64_t | objective |
| int32_t | qpsize |
| bool | use_shrinking |
| bool(* | callback )(CMKL *mkl, const float64_t *sumw, const float64_t suma) |
| CMKL * | mkl |
| CKernel * | kernel |
| CCustomKernel * | m_custom_kernel |
| CKernel * | m_kernel_backup |
| bool | use_batch_computation |
| bool | use_linadd |
| bool | use_bias |
| float64_t | m_bias |
| SGVector< float64_t > | m_alpha |
| SGVector< int32_t > | m_svs |
| float64_t | m_max_train_time |
| CLabels * | m_labels |
| ESolverType | m_solver_type |
| bool | m_store_model_features |
| bool | m_data_locked |
| CSVRLight | ( | ) |
default constructor
在文件 SVRLight.cpp 第 58 行定义.
|
virtual |
default destructor
在文件 SVRLight.cpp 第 64 行定义.
|
inherited |
apply machine to data if data is not specified apply to the current features
| data | (test)data to be classified |
在文件 Machine.cpp 第 152 行定义.
|
virtualinherited |
apply kernel machine to data for binary classification task
| data | (test)data to be classified |
重载 CMachine .
被 CDomainAdaptationSVM 重载.
在文件 KernelMachine.cpp 第 248 行定义.
|
staticinherited |
apply example helper, used in threads
| p | params of the thread |
在文件 KernelMachine.cpp 第 424 行定义.
|
virtualinherited |
apply machine to data in means of latent problem
被 CLinearLatentMachine 重载.
在文件 Machine.cpp 第 232 行定义.
Applies a locked machine on a set of indices. Error if machine is not locked
| indices | index vector (of locked features) that is predicted |
在文件 Machine.cpp 第 187 行定义.
|
virtualinherited |
Applies a locked machine on a set of indices. Error if machine is not locked. Binary case
| indices | index vector (of locked features) that is predicted |
重载 CMachine .
在文件 KernelMachine.cpp 第 518 行定义.
Applies a locked machine on a set of indices. Error if machine is not locked
| indices | index vector (of locked features) that is predicted |
在文件 KernelMachine.cpp 第 531 行定义.
|
virtualinherited |
applies a locked machine on a set of indices for latent problems
在文件 Machine.cpp 第 266 行定义.
|
virtualinherited |
applies a locked machine on a set of indices for multiclass problems
在文件 Machine.cpp 第 252 行定义.
|
virtualinherited |
Applies a locked machine on a set of indices. Error if machine is not locked. Binary case
| indices | index vector (of locked features) that is predicted |
重载 CMachine .
在文件 KernelMachine.cpp 第 524 行定义.
|
virtualinherited |
applies a locked machine on a set of indices for structured problems
在文件 Machine.cpp 第 259 行定义.
|
virtualinherited |
apply machine to data in means of multiclass classification problem
被 CNeuralNetwork, CCHAIDTree, CCARTree, CGaussianProcessClassification, CMulticlassMachine, CKNN, CC45ClassifierTree, CID3ClassifierTree, CDistanceMachine, CVwConditionalProbabilityTree, CGaussianNaiveBayes, CConditionalProbabilityTree, CMCLDA, CQDA, CRelaxedTree , 以及 CBaggingMachine 重载.
在文件 Machine.cpp 第 220 行定义.
|
virtualinherited |
apply kernel machine to one example
| num | which example to apply to |
重载 CMachine .
在文件 KernelMachine.cpp 第 405 行定义.
|
virtualinherited |
apply kernel machine to data for regression task
| data | (test)data to be classified |
重载 CMachine .
在文件 KernelMachine.cpp 第 242 行定义.
|
virtualinherited |
apply machine to data in means of SO classification problem
被 CLinearStructuredOutputMachine 重载.
在文件 Machine.cpp 第 226 行定义.
|
inherited |
Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.
| dict | dictionary of parameters to be built. |
在文件 SGObject.cpp 第 597 行定义.
|
inherited |
calculate SVM model
| docs | docs |
| label | label |
| lin | lin |
| a | a |
| a_old | old a |
| c | c |
| working2dnum | working 2D num |
| active2dnum | active 2D num |
在文件 SVMLight.cpp 第 1249 行定义.
在文件 SVMLight.cpp 第 1685 行定义.
|
inherited |
check optimality
| label | label |
| a | a |
| lin | lin |
| c | c |
| totdoc | totdoc |
| maxdiff | maximum diff |
| epsilon_crit_org | epsilon crit org |
| misclassified | misclassified |
| inconsistent | inconsistent |
| active2dnum | active 2D num |
| last_suboptimal_at | last suboptimal at |
| iteration | iteration |
在文件 SVMLight.cpp 第 1366 行定义.
|
inherited |
|
virtualinherited |
Creates a clone of the current object. This is done via recursively traversing all parameters, which corresponds to a deep copy. Calling equals on the cloned object always returns true although none of the memory of both objects overlaps.
在文件 SGObject.cpp 第 714 行定义.
|
inherited |
compute index
| binfeature | binary feature |
| range | range |
| index |
在文件 SVMLight.cpp 第 987 行定义.
|
protectedvirtual |
compute kernel at given index
| i | index i |
| j | index j |
重载 CSVMLight .
在文件 SVRLight.cpp 第 390 行定义.
|
staticprotectedinherited |
|
inherited |
compute matrices for optimization
| docs | docs |
| label | label |
| exclude_from_eq_const | exclude from eq const |
| eq_target | eq target |
| chosen | chosen |
| active2dnum | active 2D num |
| key | key |
| a | a |
| lin | lin |
| c | c |
| varnum | var num |
| totdoc | totdoc |
| aicache | ai cache |
| qp | QP |
在文件 SVMLight.cpp 第 1176 行定义.
|
inherited |
compute matrices for optimization in parallel
| docs | docs |
| label | label |
| exclude_from_eq_const | exclude from eq const |
| eq_target | eq target |
| chosen | chosen |
| active2dnum | active 2D num |
| key | key |
| a | a |
| lin | lin |
| c | c |
| varnum | var num |
| totdoc | totdoc |
| aicache | ai cache |
| qp | QP |
在文件 SVMLight.cpp 第 1044 行定义.
|
virtual |
compute objective function
| a | a |
| lin | lin |
| c | c |
| eps | eps |
| label | label |
| totdoc | totdoc |
重载 CSVMLight .
在文件 SVRLight.cpp 第 337 行定义.
|
inherited |
|
inherited |
|
inherited |
create new model
| num | number of alphas and support vectors in new model |
在文件 KernelMachine.cpp 第 194 行定义.
Locks the machine on given labels and data. After this call, only train_locked and apply_locked may be called.
Computes kernel matrix to speed up train/apply calls
| labs | labels used for locking |
| features | features used for locking |
重载 CMachine .
在文件 KernelMachine.cpp 第 623 行定义.
|
virtualinherited |
|
virtualinherited |
A deep copy. All the instance variables will also be copied.
在文件 SGObject.cpp 第 198 行定义.
Recursively compares the current SGObject to another one. Compares all registered numerical parameters, recursion upon complex (SGObject) parameters. Does not compare pointers!
May be overwritten but please do with care! Should not be necessary in most cases.
| other | object to compare with |
| accuracy | accuracy to use for comparison (optional) |
| tolerant | allows linient check on float equality (within accuracy) |
在文件 SGObject.cpp 第 618 行定义.
|
inherited |
在文件 KernelMachine.cpp 第 189 行定义.
|
inherited |
check if batch computation is enabled
在文件 KernelMachine.cpp 第 99 行定义.
|
inherited |
|
inherited |
|
virtual |
|
inherited |
|
inherited |
|
inherited |
|
inherited |
|
virtualinherited |
|
inherited |
|
protectedvirtualinherited |
|
virtualinherited |
returns type of problem machine solves
被 CNeuralNetwork, CRandomForest, CCHAIDTree, CCARTree , 以及 CBaseMulticlassMachine 重载.
|
inherited |
|
inherited |
在文件 SGObject.cpp 第 498 行定义.
|
inherited |
Returns description of a given parameter string, if it exists. SG_ERROR otherwise
| param_name | name of the parameter |
在文件 SGObject.cpp 第 522 行定义.
|
inherited |
Returns index of model selection parameter with provided index
| param_name | name of model selection parameter |
在文件 SGObject.cpp 第 535 行定义.
|
virtual |
|
inherited |
|
inherited |
|
inherited |
|
inherited |
|
inherited |
get support vector at given index
| idx | index of support vector |
在文件 KernelMachine.cpp 第 134 行定义.
|
inherited |
在文件 KernelMachine.cpp 第 184 行定义.
|
inherited |
init SVM
在文件 SVMLight.cpp 第 139 行定义.
|
inherited |
|
inherited |
init shrink state
| shrink_state | shrink state |
| totdoc | totdoc |
| maxhistory | maximum history |
在文件 SVMLight.cpp 第 1944 行定义.
|
virtualinherited |
If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.
| generic | set to the type of the generic if returning TRUE |
在文件 SGObject.cpp 第 296 行定义.
|
protectedvirtualinherited |
check whether the labels is valid.
Subclasses can override this to implement their check of label types.
| lab | the labels being checked, guaranteed to be non-NULL |
被 CNeuralNetwork, CCARTree, CCHAIDTree, CGaussianProcessRegression , 以及 CBaseMulticlassMachine 重载.
|
inherited |
|
virtualinherited |
Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!
| file | where to load from |
| prefix | prefix for members |
在文件 SGObject.cpp 第 369 行定义.
|
protectedvirtualinherited | |||||||||||||
Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_POST is called.
| ShogunException | will be thrown if an error occurs. |
被 CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel , 以及 CExponentialKernel 重载.
在文件 SGObject.cpp 第 426 行定义.
|
protectedvirtualinherited | |||||||||||||
Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_PRE is called.
| ShogunException | will be thrown if an error occurs. |
被 CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.
在文件 SGObject.cpp 第 421 行定义.
|
inherited |
problem type
| MACHINE_PROBLEM_TYPE | ( | PT_REGRESSION | ) |
problem type
|
protectedinherited |
在文件 SVMLight.cpp 第 2396 行定义.
|
inherited |
optimise SVM
| docs | docs |
| label | label |
| exclude_from_eq_const | exclude from eq const |
| eq_target | eq target |
| chosen | chosen |
| active2dnum | active 2D num |
| totdoc | totdoc |
| working2dnum | working 2D num |
| varnum | var num |
| a | a |
| lin | lin |
| c | c |
| aicache | ai cache |
| qp | QP |
| epsilon_crit_target | epsilon crit target |
在文件 SVMLight.cpp 第 1007 行定义.
|
inherited |
optimize to convergence
| docs | the docs |
| label | the label |
| totdoc | the totdoc |
| shrink_state | shrink state |
| inconsistent | inconsistent |
| a | a |
| lin | lin |
| c | c |
| timing_profile | timing profile |
| maxdiff | maximum diff |
| heldout | held out |
| retrain | retrain |
在文件 SVMLight.cpp 第 546 行定义.
|
virtualinherited |
在文件 SGObject.cpp 第 262 行定义.
|
inherited |
prints all parameter registered for model selection and their type
在文件 SGObject.cpp 第 474 行定义.
|
virtualinherited |
|
virtual |
reactivate inactive examples
| label | label |
| a | a |
| shrink_state | shrink state |
| lin | lin |
| c | c |
| totdoc | totdoc |
| iteration | iteration |
| inconsistent | inconsistent |
| docs | docs |
| aicache | ai cache |
| maxdiff | maxdiff |
重载 CSVMLight .
在文件 SVRLight.cpp 第 666 行定义.
|
staticprotectedinherited |
|
staticprotectedinherited |
|
protected |
|
staticprotected |
|
inherited |
|
virtualinherited |
Save this object to file.
| file | where to save the object; will be closed during returning if PREFIX is an empty string. |
| prefix | prefix for members |
在文件 SGObject.cpp 第 314 行定义.
|
protectedvirtualinherited | |||||||||||||
Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_POST is called.
| ShogunException | will be thrown if an error occurs. |
被 CKernel 重载.
在文件 SGObject.cpp 第 436 行定义.
|
protectedvirtualinherited | |||||||||||||
Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_PRE is called.
| ShogunException | will be thrown if an error occurs. |
被 CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.
在文件 SGObject.cpp 第 431 行定义.
|
inherited |
select next qp subproblem grad
| label | label |
| a | a |
| lin | lin |
| c | c |
| totdoc | totdoc |
| qp_size | size of qp |
| inconsistent | inconsistent |
| active2dnum | active 2D num |
| working2dnum | working 2D num |
| selcrit | selcrit |
| select | select |
| cache_only | cache only |
| key | key |
| chosen | chosen |
在文件 SVMLight.cpp 第 1746 行定义.
|
inherited |
select next qp subproblem rand
| label | label |
| a | a |
| lin | lin |
| c | c |
| totdoc | totdoc |
| qp_size | size of qp |
| inconsistent | inconsistent |
| active2dnum | active 2D num |
| working2dnum | working 2D num |
| selcrit | selcrit |
| select | select |
| key | key |
| chosen | chosen |
| iteration | iteration |
在文件 SVMLight.cpp 第 1838 行定义.
|
inherited |
|
inherited |
set alpha at given index to given value
| idx | index of alpha vector |
| val | new value of alpha vector |
在文件 KernelMachine.cpp 第 159 行定义.
set alphas to given values
| alphas | float vector with all alphas to set |
在文件 KernelMachine.cpp 第 174 行定义.
|
inherited |
set batch computation enabled
| enable | if batch computation shall be enabled |
在文件 KernelMachine.cpp 第 94 行定义.
|
inherited |
|
inherited |
|
inherited |
|
inherited |
在文件 SGObject.cpp 第 41 行定义.
|
inherited |
在文件 SGObject.cpp 第 46 行定义.
|
inherited |
在文件 SGObject.cpp 第 51 行定义.
|
inherited |
在文件 SGObject.cpp 第 56 行定义.
|
inherited |
在文件 SGObject.cpp 第 61 行定义.
|
inherited |
在文件 SGObject.cpp 第 66 行定义.
|
inherited |
在文件 SGObject.cpp 第 71 行定义.
|
inherited |
在文件 SGObject.cpp 第 76 行定义.
|
inherited |
在文件 SGObject.cpp 第 81 行定义.
|
inherited |
在文件 SGObject.cpp 第 86 行定义.
|
inherited |
在文件 SGObject.cpp 第 91 行定义.
|
inherited |
在文件 SGObject.cpp 第 96 行定义.
|
inherited |
在文件 SGObject.cpp 第 101 行定义.
|
inherited |
在文件 SGObject.cpp 第 106 行定义.
|
inherited |
在文件 SGObject.cpp 第 111 行定义.
|
inherited |
set generic type to T
|
inherited |
|
inherited |
|
inherited |
|
inherited |
|
virtualinherited |
set labels
| lab | labels |
被 CNeuralNetwork, CGaussianProcessMachine, CCARTree, CStructuredOutputMachine, CRelaxedTree , 以及 CMulticlassMachine 重载.
在文件 Machine.cpp 第 65 行定义.
|
inherited |
|
inherited |
|
inherited |
|
inherited |
|
virtualinherited |
Setter for store-model-features-after-training flag
| store_model | whether model should be stored after training |
在文件 Machine.cpp 第 107 行定义.
|
inherited |
set support vector at given index to given value
| idx | index of support vector |
| val | new value of support vector |
在文件 KernelMachine.cpp 第 149 行定义.
|
inherited |
set support vectors to given values
| svs | integer vector with all support vectors indexes to set |
在文件 KernelMachine.cpp 第 179 行定义.
|
inherited |
|
virtualinherited |
A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.
被 CGaussianKernel 重载.
在文件 SGObject.cpp 第 192 行定义.
|
inherited |
shrink problem
| shrink_state | shrink state |
| active2dnum | active 2D num |
| last_suboptimal_at | last suboptimal at |
| iteration | iteration |
| totdoc | totdoc |
| minshrink | minimal shrink |
| a | a |
| inconsistent | inconsistent |
| c | c |
| lin | lin |
| label | label |
在文件 SVMLight.cpp 第 1976 行定义.
|
inherited |
|
protectedvirtualinherited |
Stores feature data of the SV indices and sets it to the lhs of the underlying kernel. Then, all SV indices are set to identity.
May be overwritten by subclasses in case the model should be stored differently.
重载 CMachine .
在文件 KernelMachine.cpp 第 453 行定义.
|
virtualinherited |
|
inherited |
learn SVM
在文件 SVMLight.cpp 第 301 行定义.
| void svr_learn | ( | ) |
SVR learn
在文件 SVRLight.cpp 第 155 行定义.
|
virtualinherited |
train machine
| data | training data (parameter can be avoided if distance or kernel-based classifiers are used and distance/kernels are initialized with train data). If flag is set, model features will be stored after training. |
被 CRelaxedTree, CAutoencoder, CSGDQN , 以及 COnlineSVMSGD 重载.
在文件 Machine.cpp 第 39 行定义.
Trains a locked machine on a set of indices. Error if machine is not locked
| indices | index vector (of locked features) that is used for training |
重载 CMachine .
在文件 KernelMachine.cpp 第 482 行定义.
|
protectedvirtual |
train regression
| data | training data (parameter can be avoided if distance or kernel-based regressors are used and distance/kernels are initialized with train data) |
重载 CSVMLight .
在文件 SVRLight.cpp 第 73 行定义.
|
protectedvirtualinherited |
returns whether machine require labels for training
被 COnlineLinearMachine, CHierarchical, CLinearLatentMachine, CVwConditionalProbabilityTree, CConditionalProbabilityTree , 以及 CLibSVMOneClass 重载.
|
inherited |
unset generic type
this has to be called in classes specializing a template class
在文件 SGObject.cpp 第 303 行定义.
|
virtual |
update linear component
| docs | docs |
| label | label |
| active2dnum | active2dnum |
| a | a |
| a_old | a old |
| working2dnum | working2dnum |
| totdoc | totdoc |
| lin | lin |
| aicache | ai cache |
| c | c |
重载 CSVMLight .
在文件 SVRLight.cpp 第 397 行定义.
|
staticprotected |
|
virtual |
update linear component MKL
| docs | docs |
| label | label |
| active2dnum | active2dnum |
| a | a |
| a_old | a old |
| working2dnum | working2dnum |
| totdoc | totdoc |
| lin | lin |
| aicache | ai cache |
| c | c |
在文件 SVRLight.cpp 第 495 行定义.
|
inherited |
update linear component MKL
| docs | docs |
| label | label |
| active2dnum | active 2D num |
| a | a |
| a_old | old a |
| working2dnum | working 2D num |
| totdoc | totdoc |
| lin | lin |
| aicache | ai cache |
在文件 SVMLight.cpp 第 1524 行定义.
|
virtual |
update linear component MKL linadd
| docs | docs |
| label | label |
| active2dnum | active2dnum |
| a | a |
| a_old | a old |
| working2dnum | working2dnum |
| totdoc | totdoc |
| lin | lin |
| aicache | ai cache |
| c | c |
在文件 SVRLight.cpp 第 568 行定义.
|
inherited |
update linear component MKL
| docs | docs |
| label | label |
| active2dnum | active 2D num |
| a | a |
| a_old | old a |
| working2dnum | working 2D num |
| totdoc | totdoc |
| lin | lin |
| aicache | ai cache |
在文件 SVMLight.cpp 第 1598 行定义.
|
staticinherited |
|
virtualinherited |
Updates the hash of current parameter combination
在文件 SGObject.cpp 第 248 行定义.
|
protectedinherited |
number of iteration
在文件 SVMLight.h 第 681 行定义.
|
protectedinherited |
dual
在文件 SVMLight.h 第 672 行定义.
|
protectedinherited |
init iter
在文件 SVMLight.h 第 662 行定义.
|
protectedinherited |
init margin
在文件 SVMLight.h 第 660 行定义.
|
inherited |
io
在文件 SGObject.h 第 369 行定义.
|
protectedinherited |
kernel
在文件 KernelMachine.h 第 311 行定义.
|
protectedinherited |
learn parameters
在文件 SVMLight.h 第 655 行定义.
coefficients alpha
在文件 KernelMachine.h 第 332 行定义.
|
protectedinherited |
bias term b
在文件 KernelMachine.h 第 329 行定义.
|
protectedinherited |
is filled with pre-computed custom kernel on data lock
在文件 KernelMachine.h 第 314 行定义.
|
inherited |
parameters wrt which we can compute gradients
在文件 SGObject.h 第 384 行定义.
|
inherited |
Hash of parameter values
在文件 SGObject.h 第 387 行定义.
|
protectedinherited |
old kernel is stored here on data lock
在文件 KernelMachine.h 第 317 行定义.
|
inherited |
model selection parameters
在文件 SGObject.h 第 381 行定义.
|
inherited |
parameters
在文件 SGObject.h 第 378 行定义.
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
array of ``support vectors'' (indices of feature objects)
在文件 KernelMachine.h 第 335 行定义.
|
protectedinherited |
|
protectedinherited |
mkl converged
在文件 SVMLight.h 第 687 行定义.
|
protectedinherited |
model
在文件 SVMLight.h 第 653 行定义.
|
protectedinherited |
model b
在文件 SVMLight.h 第 666 行定义.
|
protectedinherited |
current alpha gap
在文件 SVMLight.h 第 683 行定义.
|
protected |
number of train elements
在文件 SVRLight.h 第 237 行定义.
|
protectedinherited |
opt precision
在文件 SVMLight.h 第 668 行定义.
|
inherited |
parallel
在文件 SGObject.h 第 372 行定义.
|
protectedinherited |
precision violations
在文件 SVMLight.h 第 664 行定义.
|
protectedinherited |
primal
在文件 SVMLight.h 第 670 行定义.
|
protectedinherited |
|
protectedinherited |
if batch computation is enabled
在文件 KernelMachine.h 第 320 行定义.
|
protectedinherited |
if bias shall be used
在文件 KernelMachine.h 第 326 行定义.
|
protectedinherited |
if kernel cache is used
在文件 SVMLight.h 第 685 行定义.
|
protectedinherited |
if linadd is enabled
在文件 KernelMachine.h 第 323 行定义.
|
protectedinherited |
verbosity level (0-4)
在文件 SVMLight.h 第 657 行定义.
|
inherited |
version
在文件 SGObject.h 第 375 行定义.
|
protectedinherited |
Matrix that stores the contribution by each kernel for each example (for current alphas)
在文件 SVMLight.h 第 679 行定义.
