SHOGUN
4.1.0
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class LibSVMMultiClass. Does one vs one classification.
Definition at line 25 of file MulticlassLibSVM.h.
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 | train_machine (CFeatures *data=NULL) |
CSVM * | svm_proto () |
SGVector< int32_t > | svm_svs () |
virtual bool | init_machines_for_apply (CFeatures *data) |
virtual bool | is_acceptable_machine (CMachine *machine) |
virtual bool | init_machine_for_train (CFeatures *data) |
virtual bool | is_ready () |
virtual CMachine * | get_machine_from_trained (CMachine *machine) |
virtual int32_t | get_num_rhs_vectors () |
virtual void | add_machine_subset (SGVector< index_t > subset) |
virtual void | remove_machine_subset () |
void | init_strategy () |
void | clear_machines () |
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) |
Protected Attributes | |
svm_problem | problem |
svm_parameter | param |
struct svm_model * | model |
LIBSVM_SOLVER_TYPE | solver_type |
float64_t | m_C |
CKernel * | m_kernel |
CMulticlassStrategy * | m_multiclass_strategy |
CMachine * | m_machine |
CDynamicObjectArray * | m_machines |
float64_t | m_max_train_time |
CLabels * | m_labels |
ESolverType | m_solver_type |
bool | m_store_model_features |
bool | m_data_locked |
CMulticlassLibSVM | ( | LIBSVM_SOLVER_TYPE | st = LIBSVM_C_SVC | ) |
default constructor
Definition at line 18 of file MulticlassLibSVM.cpp.
CMulticlassLibSVM | ( | float64_t | C, |
CKernel * | k, | ||
CLabels * | lab | ||
) |
constructor
C | constant C |
k | kernel |
lab | labels |
Definition at line 23 of file MulticlassLibSVM.cpp.
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virtual |
destructor
Definition at line 28 of file MulticlassLibSVM.cpp.
set subset to the features of the machine, deletes old one
subset | subset indices to set |
Implements CMulticlassMachine.
Definition at line 178 of file KernelMulticlassMachine.cpp.
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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apply machine to data in means of binary classification problem
Reimplemented in CKernelMachine, COnlineLinearMachine, CWDSVMOcas, CNeuralNetwork, CLinearMachine, CGaussianProcessClassification, CDomainAdaptationSVMLinear, CDomainAdaptationSVM, CPluginEstimate, and CBaggingMachine.
Definition at line 208 of file Machine.cpp.
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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 for binary problems
Reimplemented in CKernelMachine, and CMultitaskLinearMachine.
Definition at line 238 of file Machine.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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applies a locked machine on a set of indices for regression problems
Reimplemented in CKernelMachine.
Definition at line 245 of file Machine.cpp.
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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 |
classify all examples
Reimplemented from CMachine.
Reimplemented in CGaussianNaiveBayes, CMCLDA, and CQDA.
Definition at line 93 of file MulticlassMachine.cpp.
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virtualinherited |
classify all examples with multiple output
Definition at line 195 of file MulticlassMachine.cpp.
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virtualinherited |
classify one example
vec_idx |
Reimplemented from CMachine.
Reimplemented in CScatterSVM, and CGaussianNaiveBayes.
Definition at line 283 of file MulticlassMachine.cpp.
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virtualinherited |
apply machine to data in means of regression problem
Reimplemented in CKernelMachine, CWDSVMOcas, COnlineLinearMachine, CNeuralNetwork, CCHAIDTree, CStochasticGBMachine, CCARTree, CLinearMachine, CGaussianProcessRegression, and CBaggingMachine.
Definition at line 214 of file Machine.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 597 of file SGObject.cpp.
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protectedinherited |
clear machines
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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 714 of file SGObject.cpp.
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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 48 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 112 of file Machine.cpp.
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virtualinherited |
Unlocks a locked machine and restores previous state
Reimplemented in CKernelMachine.
Definition at line 143 of file Machine.cpp.
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A deep copy. All the instance variables will also be copied.
Definition at line 198 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 618 of file SGObject.cpp.
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get batch computation option of base SVM
Definition at line 146 of file MulticlassSVM.h.
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get bias enabled options of base SVM
Definition at line 136 of file MulticlassSVM.h.
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virtual |
get classifier type
Reimplemented from CMachine.
Definition at line 46 of file MulticlassLibSVM.h.
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virtualinherited |
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get linadd option of base SVM
Definition at line 141 of file MulticlassSVM.h.
get linear term of base SVM
Definition at line 95 of file MulticlassSVM.h.
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get machine
num | index of machine to get |
Definition at line 74 of file MulticlassMachine.h.
construct kernel machine from given kernel machine
Implements CMulticlassMachine.
Definition at line 168 of file KernelMulticlassMachine.cpp.
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get problem type
Reimplemented from CMachine.
Reimplemented in CCHAIDTree, and CCARTree.
Definition at line 32 of file BaseMulticlassMachine.cpp.
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Definition at line 498 of file SGObject.cpp.
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Returns description of a given parameter string, if it exists. SG_ERROR otherwise
param_name | name of the parameter |
Definition at line 522 of file SGObject.cpp.
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Returns index of model selection parameter with provided index
param_name | name of model selection parameter |
Definition at line 535 of file SGObject.cpp.
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get the type of multiclass'ness
Definition at line 114 of file MulticlassMachine.h.
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virtual |
Reimplemented from CMulticlassSVM.
Definition at line 49 of file MulticlassLibSVM.h.
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get number of machines
Definition at line 27 of file BaseMulticlassMachine.cpp.
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return number of rhs feature vectors
Implements CMulticlassMachine.
Definition at line 173 of file KernelMulticlassMachine.cpp.
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get objective of base SVM
Definition at line 130 of file MulticlassSVM.h.
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get prob output heuristic of multiclass strategy
Definition at line 145 of file MulticlassMachine.h.
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returns rejection strategy
Definition at line 124 of file MulticlassMachine.h.
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get shrinking option of base SVM
Definition at line 125 of file MulticlassSVM.h.
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virtualinherited |
get output of i-th submachine for num-th vector
i | number of submachine |
num | number of feature vector |
Definition at line 80 of file MulticlassMachine.cpp.
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virtualinherited |
get outputs of i-th submachine
i | number of submachine |
Reimplemented in CDomainAdaptationMulticlassLibLinear.
Definition at line 71 of file MulticlassMachine.cpp.
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inherited |
get SVM
num | which SVM to get |
Definition at line 76 of file MulticlassSVM.h.
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inherited |
get tube epsilon of base SVM
Definition at line 100 of file MulticlassSVM.h.
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protectedvirtualinherited |
init machine for training with kernel init
Implements CMulticlassMachine.
Definition at line 128 of file KernelMulticlassMachine.cpp.
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initializes machines (OvO, OvR) for apply
Reimplemented from CKernelMulticlassMachine.
Definition at line 73 of file MulticlassSVM.cpp.
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init strategy
Definition at line 65 of file MulticlassMachine.cpp.
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protectedvirtualinherited |
is machine an SVM instance
Reimplemented from CMulticlassMachine.
Definition at line 232 of file MulticlassSVM.h.
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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 296 of file SGObject.cpp.
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check whether the labels is valid.
lab | the labels being checked, guaranteed to be non-NULL |
Reimplemented from CMachine.
Reimplemented in CCARTree, and CCHAIDTree.
Definition at line 37 of file BaseMulticlassMachine.cpp.
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check kernel availability
Implements CMulticlassMachine.
Definition at line 160 of file KernelMulticlassMachine.cpp.
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inherited |
load a Multiclass SVM from file
svm_file | the file handle |
Definition at line 111 of file MulticlassSVM.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 369 of file SGObject.cpp.
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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. |
Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.
Definition at line 426 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::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 421 of file SGObject.cpp.
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inherited |
problem type
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virtualinherited |
Definition at line 262 of file SGObject.cpp.
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prints all parameter registered for model selection and their type
Definition at line 474 of file SGObject.cpp.
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virtualinherited |
prints registered parameters out
prefix | prefix for members |
Definition at line 308 of file SGObject.cpp.
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protectedvirtualinherited |
deletes any subset set to the features of the machine
Implements CMulticlassMachine.
Definition at line 183 of file KernelMulticlassMachine.cpp.
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inherited |
write a Multiclass SVM to a file
svm_file | the file handle |
Definition at line 259 of file MulticlassSVM.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 314 of file SGObject.cpp.
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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. |
Reimplemented in CKernel.
Definition at line 436 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 431 of file SGObject.cpp.
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set batch computation option
enable | whether batch computation should be enabled |
Definition at line 207 of file MulticlassSVM.h.
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set bias option
enable_bias | whether bias should be enabled |
Definition at line 197 of file MulticlassSVM.h.
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set C parameters
C | set regularization parameter |
Definition at line 162 of file MulticlassSVM.h.
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set default number of support vectors
num_sv | number of support vectors |
Definition at line 152 of file MulticlassSVM.h.
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Definition at line 41 of file SGObject.cpp.
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Definition at line 46 of file SGObject.cpp.
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Definition at line 51 of file SGObject.cpp.
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Definition at line 56 of file SGObject.cpp.
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Definition at line 61 of file SGObject.cpp.
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Definition at line 66 of file SGObject.cpp.
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Definition at line 71 of file SGObject.cpp.
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Definition at line 76 of file SGObject.cpp.
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Definition at line 81 of file SGObject.cpp.
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Definition at line 86 of file SGObject.cpp.
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Definition at line 91 of file SGObject.cpp.
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Definition at line 96 of file SGObject.cpp.
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Definition at line 101 of file SGObject.cpp.
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Definition at line 106 of file SGObject.cpp.
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Definition at line 111 of file SGObject.cpp.
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set generic type to T
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set the parallel object
parallel | parallel object to use |
Definition at line 241 of file SGObject.cpp.
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set the version object
version | version object to use |
Definition at line 283 of file SGObject.cpp.
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set labels
lab | labels |
Reimplemented from CMachine.
Definition at line 52 of file MulticlassMachine.cpp.
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set linadd option
enable | whether linadd should be enabled |
Definition at line 202 of file MulticlassSVM.h.
set linear term
linear_term | linear term vector |
Definition at line 157 of file MulticlassSVM.h.
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set machine
num | index of machine |
machine | machine to set |
Definition at line 59 of file MulticlassMachine.h.
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set maximum training time
t | maximimum training time |
Definition at line 82 of file Machine.cpp.
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set prob output heuristic of multiclass strategy
prob_heuris | type of probability heuristic |
Definition at line 153 of file MulticlassMachine.h.
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sets rejection strategy
rejection_strategy | rejection strategy to be set |
Definition at line 133 of file MulticlassMachine.h.
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set shrinking option
enable | whether shrinking should be enabled |
Definition at line 187 of file MulticlassSVM.h.
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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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set SVM
num | number to set |
svm | SVM to set |
Definition at line 63 of file MulticlassSVM.cpp.
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set tube epsilon value
eps | tube epsilon value |
Definition at line 177 of file MulticlassSVM.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 192 of file SGObject.cpp.
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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 20 of file KernelMulticlassMachine.cpp.
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Reimplemented in CKernelMachine, and CMultitaskLinearMachine.
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protectedinherited |
casts m_machine to SVM
Definition at line 218 of file MulticlassSVM.h.
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returns support vectors
Definition at line 223 of file MulticlassSVM.h.
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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, 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
NOT IMPLEMENTED
indices | index vector (of locked features) that is used for training |
Reimplemented in CKernelMachine, and CMultitaskLinearMachine.
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train multiclass SVM 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 32 of file MulticlassLibSVM.cpp.
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returns whether machine require labels for training
Reimplemented in COnlineLinearMachine, CHierarchical, CLinearLatentMachine, CVwConditionalProbabilityTree, CConditionalProbabilityTree, and CLibSVMOneClass.
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unset generic type
this has to be called in classes specializing a template class
Definition at line 303 of file SGObject.cpp.
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Updates the hash of current parameter combination
Definition at line 248 of file SGObject.cpp.
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io
Definition at line 369 of file SGObject.h.
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C regularization constant
Definition at line 247 of file MulticlassSVM.h.
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parameters wrt which we can compute gradients
Definition at line 384 of file SGObject.h.
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Hash of parameter values
Definition at line 387 of file SGObject.h.
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kernel
Definition at line 100 of file KernelMulticlassMachine.h.
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machine
Definition at line 208 of file MulticlassMachine.h.
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machines
Definition at line 56 of file BaseMulticlassMachine.h.
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model selection parameters
Definition at line 381 of file SGObject.h.
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type of multiclass strategy
Definition at line 205 of file MulticlassMachine.h.
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parameters
Definition at line 378 of file SGObject.h.
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SVM model
Definition at line 69 of file MulticlassLibSVM.h.
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parallel
Definition at line 372 of file SGObject.h.
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SVM parameter
Definition at line 66 of file MulticlassLibSVM.h.
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SVM problem
Definition at line 64 of file MulticlassLibSVM.h.
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solver type
Definition at line 72 of file MulticlassLibSVM.h.
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version
Definition at line 375 of file SGObject.h.