SHOGUN
v2.0.0
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Class NearestCentroid, an implementation of Nearest Shrunk Centroid classifier.
To define how close examples are NearestCentroid requires a CDistance object to work with (e.g., CEuclideanDistance ).
Definition at line 33 of file NearestCentroid.h.
Public Attributes | |
SGIO * | io |
Parallel * | parallel |
Version * | version |
Parameter * | m_parameters |
Parameter * | m_model_selection_parameters |
ParameterMap * | m_parameter_map |
uint32_t | m_hash |
Protected Member Functions | |
virtual bool | train_machine (CFeatures *data=NULL) |
virtual void | store_model_features () |
virtual bool | is_label_valid (CLabels *lab) const |
virtual bool | train_require_labels () const |
virtual TParameter * | migrate (DynArray< TParameter * > *param_base, const SGParamInfo *target) |
virtual void | one_to_one_migration_prepare (DynArray< TParameter * > *param_base, const SGParamInfo *target, TParameter *&replacement, TParameter *&to_migrate, char *old_name=NULL) |
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) |
virtual bool | update_parameter_hash () |
Static Protected Member Functions | |
static void * | run_distance_thread_lhs (void *p) |
static void * | run_distance_thread_rhs (void *p) |
Protected Attributes | |
int32_t | m_num_classes |
number of classes (i.e. number of values labels can take) | |
float64_t | m_shrinking |
Shrinking parameter. | |
CDenseFeatures< float64_t > * | m_centroids |
The centroids of the trained features. | |
bool | m_is_trained |
Tells if the classifier has been trained or not. | |
CDistance * | distance |
float64_t | m_max_train_time |
CLabels * | m_labels |
ESolverType | m_solver_type |
bool | m_store_model_features |
bool | m_data_locked |
CNearestCentroid | ( | ) |
Default constructor
Definition at line 19 of file NearestCentroid.cpp.
CNearestCentroid | ( | CDistance * | distance, |
CLabels * | trainlab | ||
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constructor
distance | distance |
trainlab | labels for training |
Definition at line 24 of file NearestCentroid.cpp.
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virtual |
Destructor
Definition at line 33 of file NearestCentroid.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.
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virtualinherited |
apply machine to data in means of binary classification problem
Reimplemented in CKernelMachine, COnlineLinearMachine, CWDSVMOcas, CLinearMachine, CDomainAdaptationSVMLinear, CDomainAdaptationSVM, and CPluginEstimate.
Definition at line 218 of file Machine.cpp.
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virtualinherited |
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.
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virtualinherited |
applies a locked machine on a set of indices for binary problems
Reimplemented in CKernelMachine, CMultitaskLinearMachine, and CMultitaskCompositeMachine.
Definition at line 248 of file Machine.cpp.
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virtualinherited |
applies a locked machine on a set of indices for latent problems
Definition at line 276 of file Machine.cpp.
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applies a locked machine on a set of indices for multiclass problems
Definition at line 262 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 255 of file Machine.cpp.
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virtualinherited |
applies a locked machine on a set of indices for structured problems
Definition at line 269 of file Machine.cpp.
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virtualinherited |
Classify all provided features. Cluster index with smallest distance to to be classified element is returned
data | (test)data to be classified |
Reimplemented from CMachine.
Reimplemented in CKNN.
Definition at line 207 of file DistanceMachine.cpp.
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virtualinherited |
Apply machine to one example. Cluster index with smallest distance to to be classified element is returned
num | which example to apply machine to |
Reimplemented from CMachine.
Reimplemented in CKNN.
Definition at line 233 of file DistanceMachine.cpp.
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virtualinherited |
apply machine to data in means of regression problem
Reimplemented in CKernelMachine, CWDSVMOcas, COnlineLinearMachine, CGaussianProcessRegression, and CLinearMachine.
Definition at line 224 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 236 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 1204 of file SGObject.cpp.
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virtualinherited |
clone
Reimplemented in CKernelMachine, and CLinearMachine.
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.
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Unlocks a locked machine and restores previous state
Reimplemented in CKernelMachine.
Definition at line 153 of file Machine.cpp.
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A deep copy. All the instance variables will also be copied.
Definition at line 131 of file SGObject.h.
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get distance functions for lhs feature vectors going from a1 to a2 and rhs feature vector b
result | array of distance values |
idx_a1 | first feature vector a1 at idx_a1 |
idx_a2 | last feature vector a2 at idx_a2 |
idx_b | feature vector b at idx_b |
Definition at line 51 of file DistanceMachine.cpp.
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get distance functions for rhs feature vectors going from b1 to b2 and lhs feature vector a
result | array of distance values |
idx_b1 | first feature vector a1 at idx_b1 |
idx_b2 | last feature vector a2 at idx_b2 |
idx_a | feature vector a at idx_a |
Definition at line 113 of file DistanceMachine.cpp.
CDenseFeatures<float64_t>* get_centroids | ( | ) | const |
Get the centroids
Definition at line 76 of file NearestCentroid.h.
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virtualinherited |
get classifier type
Reimplemented in CLaRank, CSVMLight, CLeastAngleRegression, CGaussianProcessRegression, CKernelRidgeRegression, CLibLinearMTL, CLDA, CQDA, CLibLinear, CGaussianNaiveBayes, CSVRLight, CConjugateIndex, CLinearRidgeRegression, CScatterSVM, CKNN, CLibSVR, CSGDQN, CSVMSGD, CSVMOcas, CLeastSquaresRegression, COnlineSVMSGD, CKMeans, CDomainAdaptationSVMLinear, CSubGradientLPM, CMKLMulticlass, CWDSVMOcas, CHierarchical, CLPBoost, CMKLRegression, CDomainAdaptationSVM, CMKLClassification, CMKLOneClass, CLPM, CPerceptron, CAveragedPerceptron, CNewtonSVM, CLibSVM, CSubGradientSVM, CSVMLightOneClass, CSVMLin, CGMNPSVM, CMulticlassLibSVM, CGPBTSVM, CLibSVMOneClass, CGNPPSVM, CMPDSVM, and CCPLEXSVM.
Definition at line 102 of file Machine.cpp.
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inherited |
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returns type of problem machine solves
Reimplemented in CBaseMulticlassMachine.
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inherited |
Definition at line 1108 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 1132 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 1145 of file SGObject.cpp.
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virtualinherited |
Returns the name of the SGSerializable instance. It MUST BE the CLASS NAME without the prefixed `C'.
Reimplemented from CMachine.
Reimplemented in CKNN, CKMeans, and CHierarchical.
Definition at line 85 of file DistanceMachine.h.
float64_t get_shrinking | ( | ) | const |
Get shrinking constant
Definition at line 68 of file NearestCentroid.h.
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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 278 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 CBaseMulticlassMachine.
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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.
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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.
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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 |
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.
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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 occurres. |
Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CANOVAKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.
Definition at line 1033 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 occurres. |
Definition at line 1028 of file SGObject.cpp.
MACHINE_PROBLEM_TYPE | ( | PT_MULTICLASS | ) |
problem type
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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.
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protectedvirtualinherited |
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.
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protectedvirtualinherited |
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.
post lock
Reimplemented in CMultitaskLinearMachine, and CMultitaskCompositeMachine.
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prints all parameter registered for model selection and their type
Definition at line 1084 of file SGObject.cpp.
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virtualinherited |
prints registered parameters out
prefix | prefix for members |
Definition at line 290 of file SGObject.cpp.
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staticprotectedinherited |
pthread function for compute distance values
p | thread parameter |
Definition at line 175 of file DistanceMachine.cpp.
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staticprotectedinherited |
pthread function for compute distance values
p | thread parameter |
Definition at line 191 of file DistanceMachine.cpp.
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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.
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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 occurres. |
Reimplemented in CKernel.
Definition at line 1043 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 occurres. |
Reimplemented in CKernel.
Definition at line 1038 of file SGObject.cpp.
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inherited |
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set generic type to T
Definition at line 41 of file SGObject.cpp.
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set the parallel object
parallel | parallel object to use |
Definition at line 230 of file SGObject.cpp.
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set the version object
version | version object to use |
Definition at line 265 of file SGObject.cpp.
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set labels
lab | labels |
Reimplemented in CRelaxedTree, and CMulticlassMachine.
Definition at line 75 of file Machine.cpp.
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set maximum training time
t | maximimum training time |
Definition at line 92 of file Machine.cpp.
void set_shrinking | ( | float64_t | shrinking | ) |
Set shrinking constant
shrinking | to be set |
Definition at line 60 of file NearestCentroid.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 117 of file Machine.cpp.
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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.
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Ensures cluster centers are in lhs of underlying distance
NOT IMPLEMENTED! Base method. Is called automatically after train because flag is always true for distance machines. Since every distance machine has to make sure that cluster centers are in lhs of distance variable, it is unimplemented here and HAS to be implemented in subclasses.
Reimplemented from CMachine.
Reimplemented in CKNN, CKMeans, and CHierarchical.
Definition at line 115 of file DistanceMachine.h.
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virtualinherited |
Reimplemented in CKernelMachine, CMultitaskLinearMachine, and CMultitaskCompositeMachine.
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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, CSGDQN, and COnlineSVMSGD.
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, CMultitaskLinearMachine, and CMultitaskCompositeMachine.
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train Nearest Centroid 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 CMachine.
Definition at line 49 of file NearestCentroid.cpp.
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returns whether machine require labels for training
Reimplemented in COnlineLinearMachine, CKMeans, 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 285 of file SGObject.cpp.
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Updates the hash of current parameter combination.
Definition at line 237 of file SGObject.cpp.
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the distance
Definition at line 140 of file DistanceMachine.h.
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io
Definition at line 462 of file SGObject.h.
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The centroids of the trained features.
Definition at line 107 of file NearestCentroid.h.
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Hash of parameter values
Definition at line 480 of file SGObject.h.
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Tells if the classifier has been trained or not.
Definition at line 110 of file NearestCentroid.h.
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model selection parameters
Definition at line 474 of file SGObject.h.
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number of classes (i.e. number of values labels can take)
Definition at line 101 of file NearestCentroid.h.
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map for different parameter versions
Definition at line 477 of file SGObject.h.
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parameters
Definition at line 471 of file SGObject.h.
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Shrinking parameter.
Definition at line 104 of file NearestCentroid.h.
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parallel
Definition at line 465 of file SGObject.h.
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version
Definition at line 468 of file SGObject.h.