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SHOGUN
4.2.0
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SHOGUN
4.2.0
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Class KRRNystrom implements the Nyström method for kernel ridge regression, using a low-rank approximation to the kernel matrix.
The method is equivalent to ordinary kernel ridge regression, but through projecting the data on a subset of the data points, the full kernel matrix does not need to be computed, and the resulting system of equations for the alphas is cheaper to solve.
Instead of the original linear system, the following approximate system is solved
Definition at line 64 of file KRRNystrom.h.
Public Member Functions | |
| MACHINE_PROBLEM_TYPE (PT_REGRESSION) | |
| CKRRNystrom () | |
| CKRRNystrom (float64_t tau, int32_t m, CKernel *k, CLabels *lab) | |
| virtual | ~CKRRNystrom () |
| void | set_num_rkhs_basis (int32_t m) |
| virtual const char * | get_name () const |
| virtual void | set_tau (float64_t tau) |
| void | set_epsilon (float64_t epsilon) |
| virtual bool | load (FILE *srcfile) |
| virtual bool | save (FILE *dstfile) |
| virtual EMachineType | get_classifier_type () |
| 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) |
| bool | has (const std::string &name) const |
| template<typename T > | |
| bool | has (const Tag< T > &tag) const |
| template<typename T , typename U = void> | |
| bool | has (const std::string &name) const |
| template<typename T > | |
| void | set (const Tag< T > &_tag, const T &value) |
| template<typename T , typename U = void> | |
| void | set (const std::string &name, const T &value) |
| template<typename T > | |
| T | get (const Tag< T > &_tag) const |
| template<typename T , typename U = void> | |
| T | get (const std::string &name) const |
| 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 () |
Static Public Member Functions | |
| static void * | apply_helper (void *p) |
Public Attributes | |
| SGIO * | io |
| Parallel * | parallel |
| Version * | version |
| Parameter * | m_parameters |
| Parameter * | m_model_selection_parameters |
| Parameter * | m_gradient_parameters |
| uint32_t | m_hash |
Protected Member Functions | |
| virtual bool | solve_krr_system () |
| SGVector< int32_t > | subsample_indices () |
| virtual bool | train_machine (CFeatures *data=NULL) |
| 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) |
| template<typename T > | |
| void | register_param (Tag< T > &_tag, const T &value) |
| template<typename T > | |
| void | register_param (const std::string &name, const T &value) |
Protected Attributes | |
| int32_t | m_num_rkhs_basis |
| float64_t | m_tau |
| 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 |
| CKRRNystrom | ( | ) |
Default constructor
Definition at line 41 of file KRRNystrom.cpp.
| CKRRNystrom | ( | float64_t | tau, |
| int32_t | m, | ||
| CKernel * | k, | ||
| CLabels * | lab | ||
| ) |
Constructor
| tau | regularization parameter tau |
| m | number of rows/columns to choose |
| k | kernel |
| lab | labels |
Definition at line 46 of file KRRNystrom.cpp.
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virtual |
Default destructor
Definition at line 82 of file KRRNystrom.h.
apply machine to data if data is not specified apply to the current features
| data | (test)data to be classified |
Definition at line 152 of file Machine.cpp.
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virtualinherited |
apply kernel machine to data for binary classification task
| data | (test)data to be classified |
Reimplemented from CMachine.
Reimplemented in CDomainAdaptationSVM.
Definition at line 248 of file KernelMachine.cpp.
apply get outputs
| data | features to compute outputs |
Definition at line 254 of file KernelMachine.cpp.
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staticinherited |
apply example helper, used in threads
| p | params of the thread |
Definition at line 424 of file KernelMachine.cpp.
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virtualinherited |
apply machine to data in means of latent problem
Reimplemented in CLinearLatentMachine.
Definition at line 232 of file Machine.cpp.
Applies a locked machine on a set of indices. Error if machine is not locked
| indices | index vector (of locked features) that is predicted |
Definition at line 187 of file Machine.cpp.
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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 |
Reimplemented from CMachine.
Definition at line 518 of file KernelMachine.cpp.
Applies a locked machine on a set of indices. Error if machine is not locked
| indices | index vector (of locked features) that is predicted |
Definition at line 531 of file KernelMachine.cpp.
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virtualinherited |
applies a locked machine on a set of indices for latent problems
Definition at line 266 of file Machine.cpp.
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virtualinherited |
applies a locked machine on a set of indices for multiclass problems
Definition at line 252 of file Machine.cpp.
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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 |
Reimplemented from CMachine.
Definition at line 524 of file KernelMachine.cpp.
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virtualinherited |
applies a locked machine on a set of indices for structured problems
Definition at line 259 of file Machine.cpp.
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virtualinherited |
apply machine to data in means of multiclass classification problem
Reimplemented in CNeuralNetwork, CCHAIDTree, CCARTree, CGaussianProcessClassification, CKNN, CMulticlassMachine, CC45ClassifierTree, CID3ClassifierTree, CQDA, CDistanceMachine, CVwConditionalProbabilityTree, CGaussianNaiveBayes, CConditionalProbabilityTree, CMCLDA, CRelaxedTree, and CBaggingMachine.
Definition at line 220 of file Machine.cpp.
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virtualinherited |
apply kernel machine to one example
| num | which example to apply to |
Reimplemented from CMachine.
Definition at line 405 of file KernelMachine.cpp.
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virtualinherited |
apply kernel machine to data for regression task
| data | (test)data to be classified |
Reimplemented from CMachine.
Definition at line 242 of file KernelMachine.cpp.
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virtualinherited |
apply machine to data in means of SO classification problem
Reimplemented in CLinearStructuredOutputMachine.
Definition at line 226 of file Machine.cpp.
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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. |
Definition at line 630 of file SGObject.cpp.
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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.
Definition at line 747 of file SGObject.cpp.
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inherited |
create new model
| num | number of alphas and support vectors in new model |
Definition at line 194 of file KernelMachine.cpp.
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 |
Reimplemented from CMachine.
Definition at line 623 of file KernelMachine.cpp.
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virtualinherited |
Unlocks a locked machine and restores previous state
Reimplemented from CMachine.
Definition at line 654 of file KernelMachine.cpp.
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virtualinherited |
A deep copy. All the instance variables will also be copied.
Definition at line 231 of file SGObject.cpp.
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) |
Definition at line 651 of file SGObject.cpp.
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inherited |
Getter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.
| _tag | name and type information of parameter |
Definition at line 367 of file SGObject.h.
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inherited |
Getter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.
| name | name of the parameter |
Definition at line 388 of file SGObject.h.
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inherited |
get alpha at given index
| idx | index of alpha |
Definition at line 140 of file KernelMachine.cpp.
Definition at line 189 of file KernelMachine.cpp.
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inherited |
check if batch computation is enabled
Definition at line 99 of file KernelMachine.cpp.
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inherited |
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inherited |
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virtualinherited |
get classifier type
Reimplemented from CMachine.
Definition at line 103 of file KernelRidgeRegression.h.
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inherited |
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inherited |
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inherited |
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inherited |
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virtualinherited |
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inherited |
check if linadd is enabled
Definition at line 109 of file KernelMachine.cpp.
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virtualinherited |
returns type of problem machine solves
Reimplemented in CNeuralNetwork, CRandomForest, CCHAIDTree, CCARTree, and CBaseMulticlassMachine.
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inherited |
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inherited |
Definition at line 531 of file SGObject.cpp.
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inherited |
Returns description of a given parameter string, if it exists. SG_ERROR otherwise
| param_name | name of the parameter |
Definition at line 555 of file SGObject.cpp.
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inherited |
Returns index of model selection parameter with provided index
| param_name | name of model selection parameter |
Definition at line 568 of file SGObject.cpp.
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virtual |
Reimplemented from CKernelRidgeRegression.
Definition at line 103 of file KRRNystrom.h.
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inherited |
get number of support vectors
Definition at line 169 of file KernelMachine.cpp.
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inherited |
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get support vector at given index
| idx | index of support vector |
Definition at line 134 of file KernelMachine.cpp.
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inherited |
Definition at line 184 of file KernelMachine.cpp.
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inherited |
Checks if object has a class parameter identified by a name.
| name | name of the parameter |
Definition at line 289 of file SGObject.h.
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inherited |
Checks if object has a class parameter identified by a Tag.
| tag | tag of the parameter containing name and type information |
Definition at line 301 of file SGObject.h.
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inherited |
Checks if a type exists for a class parameter identified by a name.
| name | name of the parameter |
Definition at line 312 of file SGObject.h.
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inherited |
initialise kernel optimisation
Definition at line 211 of file KernelMachine.cpp.
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inherited |
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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 |
Definition at line 329 of file SGObject.cpp.
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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 |
Reimplemented in CNeuralNetwork, CCARTree, CCHAIDTree, CGaussianProcessRegression, and CBaseMulticlassMachine.
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virtualinherited |
load regression from file
| srcfile | file to load from |
Definition at line 103 of file KernelRidgeRegression.cpp.
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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 |
Definition at line 402 of file SGObject.cpp.
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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. |
Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.
Definition at line 459 of file SGObject.cpp.
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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. |
Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.
Definition at line 454 of file SGObject.cpp.
| MACHINE_PROBLEM_TYPE | ( | PT_REGRESSION | ) |
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virtualinherited |
Definition at line 295 of file SGObject.cpp.
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inherited |
prints all parameter registered for model selection and their type
Definition at line 507 of file SGObject.cpp.
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virtualinherited |
prints registered parameters out
| prefix | prefix for members |
Definition at line 341 of file SGObject.cpp.
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protectedinherited |
Registers a class parameter which is identified by a tag. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.
| _tag | name and type information of parameter |
| value | value of the parameter |
Definition at line 439 of file SGObject.h.
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protectedinherited |
Registers a class parameter which is identified by a name. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.
| name | name of the parameter |
| value | value of the parameter along with type information |
Definition at line 452 of file SGObject.h.
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virtualinherited |
save regression to file
| dstfile | file to save to |
Definition at line 110 of file KernelRidgeRegression.cpp.
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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 |
Definition at line 347 of file SGObject.cpp.
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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. |
Reimplemented in CKernel.
Definition at line 469 of file SGObject.cpp.
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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. |
Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.
Definition at line 464 of file SGObject.cpp.
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inherited |
Setter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.
| _tag | name and type information of parameter |
| value | value of the parameter |
Definition at line 328 of file SGObject.h.
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inherited |
Setter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.
| name | name of the parameter |
| value | value of the parameter along with type information |
Definition at line 354 of file SGObject.h.
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inherited |
set alpha at given index to given value
| idx | index of alpha vector |
| val | new value of alpha vector |
Definition at line 159 of file KernelMachine.cpp.
set alphas to given values
| alphas | float vector with all alphas to set |
Definition at line 174 of file KernelMachine.cpp.
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inherited |
set batch computation enabled
| enable | if batch computation shall be enabled |
Definition at line 94 of file KernelMachine.cpp.
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inherited |
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inherited |
set state of bias
| enable_bias | if bias shall be enabled |
Definition at line 114 of file KernelMachine.cpp.
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inherited |
set convergence precision for gauss seidel method
| epsilon | new epsilon |
Definition at line 83 of file KernelRidgeRegression.h.
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inherited |
Definition at line 74 of file SGObject.cpp.
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inherited |
Definition at line 79 of file SGObject.cpp.
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inherited |
Definition at line 84 of file SGObject.cpp.
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inherited |
Definition at line 89 of file SGObject.cpp.
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inherited |
Definition at line 94 of file SGObject.cpp.
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inherited |
Definition at line 99 of file SGObject.cpp.
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inherited |
Definition at line 104 of file SGObject.cpp.
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inherited |
Definition at line 109 of file SGObject.cpp.
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inherited |
Definition at line 114 of file SGObject.cpp.
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inherited |
Definition at line 119 of file SGObject.cpp.
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inherited |
Definition at line 124 of file SGObject.cpp.
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inherited |
Definition at line 129 of file SGObject.cpp.
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inherited |
Definition at line 134 of file SGObject.cpp.
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inherited |
Definition at line 139 of file SGObject.cpp.
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inherited |
Definition at line 144 of file SGObject.cpp.
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inherited |
set generic type to T
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inherited |
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inherited |
set the parallel object
| parallel | parallel object to use |
Definition at line 274 of file SGObject.cpp.
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inherited |
set the version object
| version | version object to use |
Definition at line 316 of file SGObject.cpp.
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inherited |
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virtualinherited |
set labels
| lab | labels |
Reimplemented in CNeuralNetwork, CGaussianProcessMachine, CCARTree, CStructuredOutputMachine, CRelaxedTree, and CMulticlassMachine.
Definition at line 65 of file Machine.cpp.
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inherited |
set linadd enabled
| enable | if linadd shall be enabled |
Definition at line 104 of file KernelMachine.cpp.
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inherited |
set maximum training time
| t | maximimum training time |
Definition at line 82 of file Machine.cpp.
| void set_num_rkhs_basis | ( | int32_t | m | ) |
Set the number of columns/rows to choose
| m | new m |
Definition at line 88 of file KRRNystrom.h.
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inherited |
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virtualinherited |
Setter for store-model-features-after-training flag
| store_model | whether model should be stored after training |
Definition at line 107 of file Machine.cpp.
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inherited |
set support vector at given index to given value
| idx | index of support vector |
| val | new value of support vector |
Definition at line 149 of file KernelMachine.cpp.
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inherited |
set support vectors to given values
| svs | integer vector with all support vectors indexes to set |
Definition at line 179 of file KernelMachine.cpp.
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virtualinherited |
set regularization constant
| tau | new tau |
Definition at line 77 of file KernelRidgeRegression.h.
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virtualinherited |
A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.
Reimplemented in CGaussianKernel.
Definition at line 225 of file SGObject.cpp.
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protectedvirtual |
Train regression using the Nyström method.
Reimplemented from CKernelRidgeRegression.
Definition at line 78 of file KRRNystrom.cpp.
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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.
Reimplemented from CMachine.
Definition at line 453 of file KernelMachine.cpp.
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protected |
Sample indices to pick rows/columns from kernel matrix
Definition at line 64 of file KRRNystrom.cpp.
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virtualinherited |
Reimplemented from CMachine.
Definition at line 699 of file KernelMachine.cpp.
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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. |
Reimplemented in CRelaxedTree, CAutoencoder, CLinearMachine, CSGDQN, and COnlineSVMSGD.
Definition at line 39 of file Machine.cpp.
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 |
Reimplemented from CMachine.
Definition at line 482 of file KernelMachine.cpp.
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protectedvirtualinherited |
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) |
Reimplemented from CMachine.
Definition at line 69 of file KernelRidgeRegression.cpp.
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protectedvirtualinherited |
returns whether machine require labels for training
Reimplemented in COnlineLinearMachine, CKMeansBase, CHierarchical, CLinearLatentMachine, CVwConditionalProbabilityTree, CConditionalProbabilityTree, and CLibSVMOneClass.
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inherited |
unset generic type
this has to be called in classes specializing a template class
Definition at line 336 of file SGObject.cpp.
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virtualinherited |
Updates the hash of current parameter combination
Definition at line 281 of file SGObject.cpp.
|
inherited |
io
Definition at line 537 of file SGObject.h.
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protectedinherited |
kernel
Definition at line 311 of file KernelMachine.h.
coefficients alpha
Definition at line 332 of file KernelMachine.h.
|
protectedinherited |
bias term b
Definition at line 329 of file KernelMachine.h.
|
protectedinherited |
is filled with pre-computed custom kernel on data lock
Definition at line 314 of file KernelMachine.h.
|
protectedinherited |
|
inherited |
parameters wrt which we can compute gradients
Definition at line 552 of file SGObject.h.
|
inherited |
Hash of parameter values
Definition at line 555 of file SGObject.h.
|
protectedinherited |
old kernel is stored here on data lock
Definition at line 317 of file KernelMachine.h.
|
protectedinherited |
|
inherited |
model selection parameters
Definition at line 549 of file SGObject.h.
|
protected |
Number of columns/rows to be sampled
Definition at line 119 of file KRRNystrom.h.
|
inherited |
parameters
Definition at line 546 of file SGObject.h.
|
protectedinherited |
|
protectedinherited |
|
protectedinherited |
array of ``support vectors'' (indices of feature objects)
Definition at line 335 of file KernelMachine.h.
|
protectedinherited |
regularization parameter tau
Definition at line 135 of file KernelRidgeRegression.h.
|
inherited |
parallel
Definition at line 540 of file SGObject.h.
|
protectedinherited |
if batch computation is enabled
Definition at line 320 of file KernelMachine.h.
|
protectedinherited |
if bias shall be used
Definition at line 326 of file KernelMachine.h.
|
protectedinherited |
if linadd is enabled
Definition at line 323 of file KernelMachine.h.
|
inherited |
version
Definition at line 543 of file SGObject.h.