MKLMulticlass is a class for L1-norm multiclass MKL.
It is based on the GMNPSVM Multiclass SVM. Its own parameters are the L2 norm weight change based MKL Its termination criterion set by void set_mkl_epsilon(float64_t eps ); and the maximal number of MKL iterations set by void set_max_num_mkliters(int32_t maxnum); It passes the regularization constants C1 and C2 to GMNPSVM.
Definition at line 33 of file MKLMulticlass.h.
| CMKLMulticlass | ( | ) |
Class default Constructor
Definition at line 19 of file MKLMulticlass.cpp.
| CMKLMulticlass | ( | float64_t | C, | |
| CKernel * | k, | |||
| CLabels * | lab | |||
| ) |
Class Constructor commonly used in Shogun Toolbox
| C | constant C | |
| k | kernel | |
| lab | labels |
Definition at line 30 of file MKLMulticlass.cpp.
| ~CMKLMulticlass | ( | ) | [virtual] |
Class default Destructor
Definition at line 42 of file MKLMulticlass.cpp.
| CMKLMulticlass | ( | const CMKLMulticlass & | cm | ) | [protected] |
Class Copy Constructor protected to avoid its usage
Definition at line 50 of file MKLMulticlass.cpp.
set subset to the features of the machine, deletes old one
| subset | subset indices to set |
Implements CMulticlassMachine.
Definition at line 153 of file KernelMulticlassMachine.h.
| void addingweightsstep | ( | const std::vector< float64_t > & | curweights | ) | [protected] |
adds a constraint to the LP used in MKL
| curweights | are the current MKL weights |
it uses void addingweightsstep( const std::vector<float64_t> & curweights); and float64_t getsumofsignfreealphas();
Definition at line 207 of file MKLMulticlass.cpp.
apply machine to data if data is not specified apply to the current features
| data | (test)data to be classified |
Definition at line 162 of file Machine.cpp.
| CBinaryLabels * apply_binary | ( | CFeatures * | data = NULL |
) | [virtual, inherited] |
apply machine to data in means of binary classification problem
Reimplemented in CPluginEstimate, CWDSVMOcas, CKernelMachine, CLinearMachine, COnlineLinearMachine, CDomainAdaptationSVM, and CDomainAdaptationSVMLinear.
Definition at line 218 of file Machine.cpp.
| CLatentLabels * apply_latent | ( | CFeatures * | data = NULL |
) | [virtual, inherited] |
apply machine to data in means of latent problem
Reimplemented in CLinearLatentMachine.
Definition at line 242 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 197 of file Machine.cpp.
| CBinaryLabels * apply_locked_binary | ( | SGVector< index_t > | indices | ) | [virtual, inherited] |
applies a locked machine on a set of indices for binary problems
Reimplemented in CKernelMachine, CMultitaskCompositeMachine, and CMultitaskLinearMachine.
Definition at line 248 of file Machine.cpp.
| CLatentLabels * apply_locked_latent | ( | SGVector< index_t > | indices | ) | [virtual, inherited] |
applies a locked machine on a set of indices for latent problems
Definition at line 276 of file Machine.cpp.
| CMulticlassLabels * apply_locked_multiclass | ( | SGVector< index_t > | indices | ) | [virtual, inherited] |
applies a locked machine on a set of indices for multiclass problems
Definition at line 262 of file Machine.cpp.
| CRegressionLabels * apply_locked_regression | ( | SGVector< index_t > | indices | ) | [virtual, inherited] |
applies a locked machine on a set of indices for regression problems
Reimplemented in CKernelMachine.
Definition at line 255 of file Machine.cpp.
| CStructuredLabels * apply_locked_structured | ( | SGVector< index_t > | indices | ) | [virtual, inherited] |
applies a locked machine on a set of indices for structured problems
Definition at line 269 of file Machine.cpp.
| CMulticlassLabels * apply_multiclass | ( | CFeatures * | data = NULL |
) | [virtual, inherited] |
classify all examples
Reimplemented from CMachine.
Reimplemented in CGaussianNaiveBayes, and CQDA.
Definition at line 92 of file MulticlassMachine.cpp.
| CMulticlassMultipleOutputLabels * apply_multiclass_multiple_output | ( | CFeatures * | data = NULL, |
|
| int32_t | n_outputs = 5 | |||
| ) | [virtual, inherited] |
classify all examples with multiple output
Definition at line 146 of file MulticlassMachine.cpp.
| float64_t apply_one | ( | int32_t | vec_idx | ) | [virtual, inherited] |
classify one example
| vec_idx |
Reimplemented from CMachine.
Reimplemented in CGaussianNaiveBayes.
Definition at line 234 of file MulticlassMachine.cpp.
| CRegressionLabels * apply_regression | ( | CFeatures * | data = NULL |
) | [virtual, inherited] |
apply machine to data in means of regression problem
Reimplemented in CWDSVMOcas, CKernelMachine, CLinearMachine, COnlineLinearMachine, and CGaussianProcessRegression.
Definition at line 224 of file Machine.cpp.
| CStructuredLabels * apply_structured | ( | CFeatures * | data = NULL |
) | [virtual, inherited] |
apply machine to data in means of SO classification problem
Reimplemented in CLinearStructuredOutputMachine.
Definition at line 236 of file Machine.cpp.
| void build_parameter_dictionary | ( | CMap< TParameter *, CSGObject * > & | dict | ) | [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 1201 of file SGObject.cpp.
| void clear_machines | ( | ) | [protected, inherited] |
clear machines
Reimplemented in CNativeMulticlassMachine.
| virtual CMachine* clone | ( | ) | [virtual, inherited] |
clone
Reimplemented in CKernelMachine, and CLinearMachine.
| bool create_multiclass_svm | ( | int32_t | num_classes | ) | [inherited] |
create multiclass SVM. Appends the appropriate number of svm pointer (depending on multiclass strategy) to m_machines. All pointers are initialized with NULL.
| num_classes | number of classes in SVM |
Definition at line 46 of file MulticlassSVM.cpp.
Locks the machine on given labels and data. After this call, only train_locked and apply_locked may be called
Only possible if supports_locking() returns true
| labs | labels used for locking | |
| features | features used for locking |
Reimplemented in CKernelMachine.
Definition at line 122 of file Machine.cpp.
| void data_unlock | ( | ) | [virtual, inherited] |
Unlocks a locked machine and restores previous state
Reimplemented in CKernelMachine.
Definition at line 153 of file Machine.cpp.
| virtual CSGObject* deep_copy | ( | ) | const [virtual, inherited] |
A deep copy. All the instance variables will also be copied.
Definition at line 131 of file SGObject.h.
| bool evaluatefinishcriterion | ( | const int32_t | numberofsilpiterations | ) | [protected, virtual] |
checks MKL for convergence
| numberofsilpiterations | is the number of currently done iterations |
Definition at line 131 of file MKLMulticlass.cpp.
| bool get_batch_computation_enabled | ( | ) | [inherited] |
get batch computation option of base SVM
Definition at line 144 of file MulticlassSVM.h.
| bool get_bias_enabled | ( | ) | [inherited] |
get bias enabled options of base SVM
Definition at line 134 of file MulticlassSVM.h.
| float64_t get_C | ( | ) | [inherited] |
| virtual EMachineType get_classifier_type | ( | ) | [virtual] |
get classifier type
Reimplemented from CMachine.
Definition at line 57 of file MKLMulticlass.h.
| float64_t get_epsilon | ( | ) | [inherited] |
| SGIO * get_global_io | ( | ) | [inherited] |
| Parallel * get_global_parallel | ( | ) | [inherited] |
| Version * get_global_version | ( | ) | [inherited] |
| CKernel* get_kernel | ( | ) | [inherited] |
| CLabels * get_labels | ( | ) | [virtual, inherited] |
| bool get_linadd_enabled | ( | ) | [inherited] |
get linadd option of base SVM
Definition at line 139 of file MulticlassSVM.h.
get linear term of base SVM
Definition at line 93 of file MulticlassSVM.h.
| CMachine* get_machine | ( | int32_t | num | ) | const [inherited] |
get machine
| num | index of machine to get |
Definition at line 71 of file MulticlassMachine.h.
construct kernel machine from given kernel machine
Implements CMulticlassMachine.
Definition at line 138 of file KernelMulticlassMachine.h.
| virtual EProblemType get_machine_problem_type | ( | ) | const [virtual, inherited] |
get problem type
Reimplemented from CMachine.
Definition at line 46 of file BaseMulticlassMachine.h.
| float64_t get_max_train_time | ( | ) | [inherited] |
| SGStringList< char > get_modelsel_names | ( | ) | [inherited] |
Definition at line 1108 of file SGObject.cpp.
| char * get_modsel_param_descr | ( | const char * | param_name | ) | [inherited] |
Returns description of a given parameter string, if it exists. SG_ERROR otherwise
| param_name | name of the parameter |
Definition at line 1132 of file SGObject.cpp.
| index_t get_modsel_param_index | ( | const char * | param_name | ) | [inherited] |
Returns index of model selection parameter with provided index
| param_name | name of model selection parameter |
Definition at line 1145 of file SGObject.cpp.
| CMulticlassStrategy* get_multiclass_strategy | ( | ) | const [inherited] |
get the type of multiclass'ness
Definition at line 111 of file MulticlassMachine.h.
| virtual const char* get_name | ( | ) | const [protected, virtual] |
Reimplemented from CKernelMulticlassMachine.
Definition at line 166 of file MKLMulticlass.h.
| float64_t get_nu | ( | ) | [inherited] |
| int32_t get_num_machines | ( | ) | const [inherited] |
get number of machines
Definition at line 40 of file BaseMulticlassMachine.h.
| virtual int32_t get_num_rhs_vectors | ( | ) | [protected, virtual, inherited] |
return number of rhs feature vectors
Implements CMulticlassMachine.
Definition at line 144 of file KernelMulticlassMachine.h.
| float64_t get_objective | ( | ) | [inherited] |
get objective of base SVM
Definition at line 128 of file MulticlassSVM.h.
| int32_t get_qpsize | ( | ) | [inherited] |
| CRejectionStrategy* get_rejection_strategy | ( | ) | const [inherited] |
returns rejection strategy
Definition at line 121 of file MulticlassMachine.h.
| bool get_shrinking_enabled | ( | ) | [inherited] |
get shrinking option of base SVM
Definition at line 123 of file MulticlassSVM.h.
| ESolverType get_solver_type | ( | ) | [inherited] |
| float64_t get_submachine_output | ( | int32_t | i, | |
| int32_t | num | |||
| ) | [virtual, inherited] |
get output of i-th submachine for num-th vector
| i | number of submachine | |
| num | number of feature vector |
Definition at line 79 of file MulticlassMachine.cpp.
| CBinaryLabels * get_submachine_outputs | ( | int32_t | i | ) | [virtual, inherited] |
get outputs of i-th submachine
| i | number of submachine |
Reimplemented in CDomainAdaptationMulticlassLibLinear.
Definition at line 70 of file MulticlassMachine.cpp.
| CSVM* get_svm | ( | int32_t | num | ) | [inherited] |
get SVM
| num | which SVM to get |
Definition at line 74 of file MulticlassSVM.h.
| float64_t get_tube_epsilon | ( | ) | [inherited] |
get tube epsilon of base SVM
Definition at line 98 of file MulticlassSVM.h.
| float64_t getsquarenormofprimalcoefficients | ( | const int32_t | ind | ) | [protected] |
computes the second svm-dependent part used for generating MKL constraints
| ind | is the index of the kernel for which to compute  |
Definition at line 286 of file MKLMulticlass.cpp.
| float64_t * getsubkernelweights | ( | int32_t & | numweights | ) |
returns MKL weights for the different kernels
| numweights | is output parameter, is set to zero if no weights have been computed or to the number of MKL weights which is equal to the number of kernels |
Definition at line 404 of file MKLMulticlass.cpp.
| float64_t getsumofsignfreealphas | ( | ) | [protected] |
computes the first svm-dependent part used for generating MKL constraints it is 
Definition at line 240 of file MKLMulticlass.cpp.
| virtual bool init_machine_for_train | ( | CFeatures * | data | ) | [protected, virtual, inherited] |
init machine for training with kernel init
Implements CMulticlassMachine.
Definition at line 95 of file KernelMulticlassMachine.h.
| bool init_machines_for_apply | ( | CFeatures * | data | ) | [protected, virtual, inherited] |
initializes machines (OvO, OvR) for apply
Reimplemented from CKernelMulticlassMachine.
Definition at line 71 of file MulticlassSVM.cpp.
| void init_strategy | ( | ) | [protected, inherited] |
init strategy
Reimplemented in CNativeMulticlassMachine.
Definition at line 64 of file MulticlassMachine.cpp.
| void initlpsolver | ( | ) | [protected] |
performs some sanity checks (on the provided kernel), inits the GLPK-based LP solver
Definition at line 92 of file MKLMulticlass.cpp.
| void initsvm | ( | ) | [protected] |
inits the underlying Multiclass SVM
Definition at line 69 of file MKLMulticlass.cpp.
| virtual bool is_acceptable_machine | ( | CMachine * | machine | ) | [protected, virtual, inherited] |
is machine an SVM instance
Reimplemented from CMulticlassMachine.
Definition at line 224 of file MulticlassSVM.h.
| bool is_data_locked | ( | ) | const [inherited] |
| bool is_generic | ( | EPrimitiveType * | generic | ) | const [virtual, inherited] |
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 278 of file SGObject.cpp.
| virtual bool is_label_valid | ( | CLabels * | lab | ) | const [virtual, inherited] |
check whether the labels is valid.
| lab | the labels being checked, guaranteed to be non-NULL |
Reimplemented from CMachine.
Definition at line 55 of file BaseMulticlassMachine.h.
| virtual bool is_ready | ( | ) | [protected, virtual, inherited] |
check kernel availability
Implements CMulticlassMachine.
Definition at line 129 of file KernelMulticlassMachine.h.
| bool load | ( | FILE * | svm_file | ) | [inherited] |
load a Multiclass SVM from file
| svm_file | the file handle |
Definition at line 109 of file MulticlassSVM.cpp.
| DynArray< TParameter * > * load_all_file_parameters | ( | int32_t | file_version, | |
| int32_t | current_version, | |||
| CSerializableFile * | file, | |||
| const char * | prefix = "" | |||
| ) | [inherited] |
maps all parameters of this instance to the provided file version and loads all parameter data from the file into an array, which is sorted (basically calls load_file_parameter(...) for all parameters and puts all results into a sorted array)
| file_version | parameter version of the file | |
| current_version | version from which mapping begins (you want to use VERSION_PARAMETER for this in most cases) | |
| file | file to load from | |
| prefix | prefix for members |
Definition at line 679 of file SGObject.cpp.
| DynArray< TParameter * > * load_file_parameters | ( | const SGParamInfo * | param_info, | |
| int32_t | file_version, | |||
| CSerializableFile * | file, | |||
| const char * | prefix = "" | |||
| ) | [inherited] |
loads some specified parameters from a file with a specified version The provided parameter info has a version which is recursively mapped until the file parameter version is reached. Note that there may be possibly multiple parameters in the mapping, therefore, a set of TParameter instances is returned
| param_info | information of parameter | |
| file_version | parameter version of the file, must be <= provided parameter version | |
| file | file to load from | |
| prefix | prefix for members |
Definition at line 523 of file SGObject.cpp.
| bool load_serializable | ( | CSerializableFile * | file, | |
| const char * | prefix = "", |
|||
| int32_t | param_version = VERSION_PARAMETER | |||
| ) | [virtual, inherited] |
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 | |
| param_version | (optional) a parameter version different to (this is mainly for testing, better do not use) |
Reimplemented in CModelSelectionParameters.
Definition at line 354 of file SGObject.cpp.
| void load_serializable_post | ( | ) | throw (ShogunException) [protected, virtual, inherited] |
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 occurres. |
Reimplemented in CLinearHMM, CAlphabet, CANOVAKernel, CCircularKernel, CExponentialKernel, CGaussianKernel, CInverseMultiQuadricKernel, CKernel, CWeightedDegreePositionStringKernel, and CList.
Definition at line 1033 of file SGObject.cpp.
| void load_serializable_pre | ( | ) | throw (ShogunException) [protected, virtual, inherited] |
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 occurres. |
Definition at line 1028 of file SGObject.cpp.
| MACHINE_PROBLEM_TYPE | ( | PT_MULTICLASS | ) | [inherited] |
problem type
| void map_parameters | ( | DynArray< TParameter * > * | param_base, | |
| int32_t & | base_version, | |||
| DynArray< const SGParamInfo * > * | target_param_infos | |||
| ) | [inherited] |
Takes a set of TParameter instances (base) with a certain version and a set of target parameter infos and recursively maps the base level wise to the current version using CSGObject::migrate(...). The base is replaced. After this call, the base version containing parameters should be of same version/type as the initial target parameter infos. Note for this to work, the migrate methods and all the internal parameter mappings have to match
| param_base | set of TParameter instances that are mapped to the provided target parameter infos | |
| base_version | version of the parameter base | |
| target_param_infos | set of SGParamInfo instances that specify the target parameter base |
Definition at line 717 of file SGObject.cpp.
| TParameter * migrate | ( | DynArray< TParameter * > * | param_base, | |
| const SGParamInfo * | target | |||
| ) | [protected, virtual, inherited] |
creates a new TParameter instance, which contains migrated data from the version that is provided. The provided parameter data base is used for migration, this base is a collection of all parameter data of the previous version. Migration is done FROM the data in param_base TO the provided param info Migration is always one version step. Method has to be implemented in subclasses, if no match is found, base method has to be called.
If there is an element in the param_base which equals the target, a copy of the element is returned. This represents the case when nothing has changed and therefore, the migrate method is not overloaded in a subclass
| param_base | set of TParameter instances to use for migration | |
| target | parameter info for the resulting TParameter |
Definition at line 923 of file SGObject.cpp.
| void one_to_one_migration_prepare | ( | DynArray< TParameter * > * | param_base, | |
| const SGParamInfo * | target, | |||
| TParameter *& | replacement, | |||
| TParameter *& | to_migrate, | |||
| char * | old_name = NULL | |||
| ) | [protected, virtual, inherited] |
This method prepares everything for a one-to-one parameter migration. One to one here means that only ONE element of the parameter base is needed for the migration (the one with the same name as the target). Data is allocated for the target (in the type as provided in the target SGParamInfo), and a corresponding new TParameter instance is written to replacement. The to_migrate pointer points to the single needed TParameter instance needed for migration. If a name change happened, the old name may be specified by old_name. In addition, the m_delete_data flag of to_migrate is set to true. So if you want to migrate data, the only thing to do after this call is converting the data in the m_parameter fields. If unsure how to use - have a look into an example for this. (base_migration_type_conversion.cpp for example)
| param_base | set of TParameter instances to use for migration | |
| target | parameter info for the resulting TParameter | |
| replacement | (used as output) here the TParameter instance which is returned by migration is created into | |
| to_migrate | the only source that is used for migration | |
| old_name | with this parameter, a name change may be specified |
Definition at line 864 of file SGObject.cpp.
| CMKLMulticlass operator= | ( | const CMKLMulticlass & | cm | ) | [protected] |
Class Assignment operator protected to avoid its usage
Definition at line 60 of file MKLMulticlass.cpp.
post lock
Reimplemented in CMultitaskCompositeMachine, and CMultitaskLinearMachine.
| void print_modsel_params | ( | ) | [inherited] |
prints all parameter registered for model selection and their type
Definition at line 1084 of file SGObject.cpp.
| void print_serializable | ( | const char * | prefix = "" |
) | [virtual, inherited] |
prints registered parameters out
| prefix | prefix for members |
Definition at line 290 of file SGObject.cpp.
| virtual void remove_machine_subset | ( | ) | [protected, virtual, inherited] |
deletes any subset set to the features of the machine
Implements CMulticlassMachine.
Definition at line 159 of file KernelMulticlassMachine.h.
| bool save | ( | FILE * | svm_file | ) | [inherited] |
write a Multiclass SVM to a file
| svm_file | the file handle |
Definition at line 257 of file MulticlassSVM.cpp.
| bool save_serializable | ( | CSerializableFile * | file, | |
| const char * | prefix = "", |
|||
| int32_t | param_version = VERSION_PARAMETER | |||
| ) | [virtual, inherited] |
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 | |
| param_version | (optional) a parameter version different to (this is mainly for testing, better do not use) |
Reimplemented in CModelSelectionParameters.
Definition at line 296 of file SGObject.cpp.
| void save_serializable_post | ( | ) | throw (ShogunException) [protected, virtual, inherited] |
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 occurres. |
Reimplemented in CKernel.
Definition at line 1043 of file SGObject.cpp.
| void save_serializable_pre | ( | ) | throw (ShogunException) [protected, virtual, inherited] |
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 occurres. |
Reimplemented in CKernel.
Definition at line 1038 of file SGObject.cpp.
| void set_batch_computation_enabled | ( | bool | enable | ) | [inherited] |
set batch computation option
| enable | whether batch computation should be enabled |
Definition at line 205 of file MulticlassSVM.h.
| void set_bias_enabled | ( | bool | enable_bias | ) | [inherited] |
set bias option
| enable_bias | whether bias should be enabled |
Definition at line 195 of file MulticlassSVM.h.
| void set_C | ( | float64_t | C | ) | [inherited] |
set C parameters
| C | set regularization parameter |
Definition at line 160 of file MulticlassSVM.h.
| void set_defaults | ( | int32_t | num_sv = 0 |
) | [inherited] |
set default number of support vectors
| num_sv | number of support vectors |
Definition at line 150 of file MulticlassSVM.h.
| void set_epsilon | ( | float64_t | eps | ) | [inherited] |
| void set_generic< floatmax_t > | ( | ) | [inherited] |
set generic type to T
| void set_global_io | ( | SGIO * | io | ) | [inherited] |
| void set_global_parallel | ( | Parallel * | parallel | ) | [inherited] |
set the parallel object
| parallel | parallel object to use |
Definition at line 230 of file SGObject.cpp.
| void set_global_version | ( | Version * | version | ) | [inherited] |
set the version object
| version | version object to use |
Definition at line 265 of file SGObject.cpp.
| void set_kernel | ( | CKernel * | k | ) | [inherited] |
| void set_labels | ( | CLabels * | lab | ) | [virtual, inherited] |
set labels
| lab | labels |
Reimplemented from CMachine.
Definition at line 51 of file MulticlassMachine.cpp.
| void set_linadd_enabled | ( | bool | enable | ) | [inherited] |
set linadd option
| enable | whether linadd should be enabled |
Definition at line 200 of file MulticlassSVM.h.
set linear term
| linear_term | linear term vector |
Definition at line 155 of file MulticlassSVM.h.
| bool set_machine | ( | int32_t | num, | |
| CMachine * | machine | |||
| ) | [inherited] |
set machine
| num | index of machine | |
| machine | machine to set |
Definition at line 56 of file MulticlassMachine.h.
| void set_max_num_mkliters | ( | int32_t | maxnum | ) |
sets maximal number of MKL iterations
| maxnum | is the desired maximal number of MKL iterations; when it is reached the MKL terminates irrespective of the MKL progress set it to a nonpositive value in order to turn it off |
Definition at line 425 of file MKLMulticlass.cpp.
| void set_max_train_time | ( | float64_t | t | ) | [inherited] |
set maximum training time
| t | maximimum training time |
Definition at line 92 of file Machine.cpp.
| void set_mkl_epsilon | ( | float64_t | eps | ) |
sets MKL termination threshold
| eps | is the desired threshold value the termination criterion is the L2 norm between the current MKL weights and their counterpart from the previous iteration |
Definition at line 420 of file MKLMulticlass.cpp.
| void set_mkl_norm | ( | float64_t | norm | ) | [virtual] |
| void set_nu | ( | float64_t | nue | ) | [inherited] |
| void set_objective | ( | float64_t | v | ) | [inherited] |
| void set_qpsize | ( | int32_t | qps | ) | [inherited] |
| void set_rejection_strategy | ( | CRejectionStrategy * | rejection_strategy | ) | [inherited] |
sets rejection strategy
| rejection_strategy | rejection strategy to be set |
Definition at line 130 of file MulticlassMachine.h.
| void set_shrinking_enabled | ( | bool | enable | ) | [inherited] |
set shrinking option
| enable | whether shrinking should be enabled |
Definition at line 185 of file MulticlassSVM.h.
| void set_solver_type | ( | ESolverType | st | ) | [inherited] |
| void set_store_model_features | ( | bool | store_model | ) | [virtual, inherited] |
Setter for store-model-features-after-training flag
| store_model | whether model should be stored after training |
Definition at line 117 of file Machine.cpp.
| bool set_svm | ( | int32_t | num, | |
| CSVM * | svm | |||
| ) | [inherited] |
set SVM
| num | number to set | |
| svm | SVM to set |
Definition at line 61 of file MulticlassSVM.cpp.
| void set_tube_epsilon | ( | float64_t | eps | ) | [inherited] |
set tube epsilon value
| eps | tube epsilon value |
Definition at line 175 of file MulticlassSVM.h.
| virtual CSGObject* shallow_copy | ( | ) | const [virtual, inherited] |
A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.
Reimplemented in CGaussianKernel.
Definition at line 122 of file SGObject.h.
| void store_model_features | ( | ) | [virtual, inherited] |
Stores feature data of underlying model.
Need to store the SVs for all sub-machines. We make a union of the SVs for all sub-machines, store the union and adjust the sub-machines to index into the union.
Reimplemented from CMachine.
Definition at line 17 of file KernelMulticlassMachine.cpp.
| virtual bool supports_locking | ( | ) | const [virtual, inherited] |
Reimplemented in CKernelMachine, CMultitaskCompositeMachine, and CMultitaskLinearMachine.
| CSVM* svm_proto | ( | ) | [protected, inherited] |
casts m_machine to SVM
Definition at line 210 of file MulticlassSVM.h.
| SGVector<int32_t> svm_svs | ( | ) | [protected, inherited] |
returns support vectors
Definition at line 215 of file MulticlassSVM.h.
| bool train | ( | CFeatures * | data = NULL |
) | [virtual, inherited] |
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 COnlineSVMSGD, CSGDQN, and CRelaxedTree.
Definition at line 49 of file Machine.cpp.
Trains a locked machine on a set of indices. Error if machine is not locked
NOT IMPLEMENTED
| indices | index vector (of locked features) that is used for training |
Reimplemented in CKernelMachine, CMultitaskCompositeMachine, and CMultitaskLinearMachine.
| bool train_machine | ( | CFeatures * | data = NULL |
) | [protected, virtual] |
train Multiclass MKL classifier
| data | training data (parameter can be avoided if distance or kernel-based classifiers are used and distance/kernels are initialized with train data) |
Reimplemented from CMulticlassMachine.
Definition at line 322 of file MKLMulticlass.cpp.
| virtual bool train_require_labels | ( | ) | const [protected, virtual, inherited] |
returns whether machine require labels for training
Reimplemented in CLibSVMOneClass, CHierarchical, CKMeans, CLinearLatentMachine, COnlineLinearMachine, CConditionalProbabilityTree, and CVwConditionalProbabilityTree.
| void unset_generic | ( | ) | [inherited] |
unset generic type
this has to be called in classes specializing a template class
Definition at line 285 of file SGObject.cpp.
| bool update_parameter_hash | ( | ) | [protected, virtual, inherited] |
Updates the hash of current parameter combination.
Definition at line 237 of file SGObject.cpp.
io
Definition at line 462 of file SGObject.h.
MKLMulticlassOptimizationBase* lpw [protected] |
the solver wrapper
Definition at line 177 of file MKLMulticlass.h.
C regularization constant
Definition at line 239 of file MulticlassSVM.h.
bool m_data_locked [protected, inherited] |
uint32_t m_hash [inherited] |
Hash of parameter values
Definition at line 480 of file SGObject.h.
kernel
Definition at line 167 of file KernelMulticlassMachine.h.
machine
Definition at line 191 of file MulticlassMachine.h.
CDynamicObjectArray* m_machines [protected, inherited] |
machines
Definition at line 62 of file BaseMulticlassMachine.h.
float64_t m_max_train_time [protected, inherited] |
Parameter* m_model_selection_parameters [inherited] |
model selection parameters
Definition at line 474 of file SGObject.h.
CMulticlassStrategy* m_multiclass_strategy [protected, inherited] |
type of multiclass strategy
Definition at line 188 of file MulticlassMachine.h.
ParameterMap* m_parameter_map [inherited] |
map for different parameter versions
Definition at line 477 of file SGObject.h.
Parameter* m_parameters [inherited] |
parameters
Definition at line 471 of file SGObject.h.
ESolverType m_solver_type [protected, inherited] |
bool m_store_model_features [protected, inherited] |
int32_t max_num_mkl_iters [protected] |
maximal number of MKL iterations is set by void set_max_num_mkliters(int32_t maxnum);
Definition at line 190 of file MKLMulticlass.h.
MKL termination threshold is set void set_mkl_epsilon(float64_t eps );
Definition at line 186 of file MKLMulticlass.h.
std::vector<float64_t> normweightssquared [protected] |
stores the term \| w_l \|^2 ~~~ "alpha o Y K_l Y o alpha"
Definition at line 198 of file MKLMulticlass.h.
parallel
Definition at line 465 of file SGObject.h.
MKL norm >=1
Definition at line 194 of file MKLMulticlass.h.
the multiclass svm for fixed MKL weights
Definition at line 173 of file MKLMulticlass.h.
version
Definition at line 468 of file SGObject.h.
::std::vector< std::vector< float64_t> > weightshistory [protected] |
stores the last two mkl iteration weights
Definition at line 181 of file MKLMulticlass.h.
