SHOGUN
4.2.0
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class ID3ClassifierTree, implements classifier tree for discrete feature values using the ID3 algorithm. The training algorithm implemented is as follows :
function ID3 (R: a set of non-categorical attributes, C: the categorical attribute, S: a training set)
returns a decision tree;
begin
If S consists of records all with the same value for the categorical attribute,
return a single node with that value;
If R is empty,
return a single node with as value the most frequent of the values of the categorical attribute that are found in records of S;
[note that then there will be errors, that is, records that will be improperly classified];
Let D be the attribute with largest Gain(D,S) among attributes in R;
Let \({d_j| j=1,2, .., m}\) be the values of attribute D;
Let \({S_j| j=1,2, .., m}\) be the subsets of S consisting respectively of records with value dj for attribute D;
Return a tree with root labeled D and arcs labeled \(d_1, d_2, .., d_m\) going respectively to the trees
ID3(R-{D}, C, \(S_1\)), .., ID3(R-{D}, C, \(S_m\));
end ID3;
Definition at line 74 of file ID3ClassifierTree.h.
Public Types | |
typedef CTreeMachineNode < id3TreeNodeData > | node_t |
typedef CBinaryTreeMachineNode < id3TreeNodeData > | bnode_t |
Public Member Functions | |
CID3ClassifierTree () | |
virtual | ~CID3ClassifierTree () |
virtual const char * | get_name () const |
virtual CMulticlassLabels * | apply_multiclass (CFeatures *data=NULL) |
bool | prune_tree (CDenseFeatures< float64_t > *validation_data, CMulticlassLabels *validation_labels, float64_t epsilon=0.f) |
void | set_root (CTreeMachineNode< id3TreeNodeData > *root) |
CTreeMachineNode < id3TreeNodeData > * | get_root () |
CTreeMachine * | clone_tree () |
int32_t | get_num_machines () const |
virtual EProblemType | get_machine_problem_type () const |
virtual bool | is_label_valid (CLabels *lab) const |
virtual bool | train (CFeatures *data=NULL) |
virtual CLabels * | apply (CFeatures *data=NULL) |
virtual CBinaryLabels * | apply_binary (CFeatures *data=NULL) |
virtual CRegressionLabels * | apply_regression (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 () |
virtual EMachineType | get_classifier_type () |
void | set_solver_type (ESolverType st) |
ESolverType | get_solver_type () |
virtual void | set_store_model_features (bool store_model) |
virtual bool | train_locked (SGVector< index_t > indices) |
virtual float64_t | apply_one (int32_t i) |
virtual CLabels * | apply_locked (SGVector< index_t > indices) |
virtual CBinaryLabels * | apply_locked_binary (SGVector< index_t > indices) |
virtual CRegressionLabels * | apply_locked_regression (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 | data_lock (CLabels *labs, CFeatures *features) |
virtual void | post_lock (CLabels *labs, CFeatures *features) |
virtual void | data_unlock () |
virtual bool | supports_locking () const |
bool | is_data_locked () 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 () |
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) |
virtual void | store_model_features () |
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 | |
CTreeMachineNode < id3TreeNodeData > * | m_root |
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 |
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inherited |
bnode_t type- Tree node with max 2 possible children
Definition at line 55 of file TreeMachine.h.
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inherited |
node_t type- Tree node with many possible children
Definition at line 52 of file TreeMachine.h.
constructor
Definition at line 40 of file ID3ClassifierTree.cpp.
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virtual |
destructor
Definition at line 45 of file ID3ClassifierTree.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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virtualinherited |
apply machine to data in means of binary classification problem
Reimplemented in CKernelMachine, COnlineLinearMachine, CNeuralNetwork, CLinearMachine, CGaussianProcessClassification, CDomainAdaptationSVMLinear, CDomainAdaptationSVM, CPluginEstimate, and CBaggingMachine.
Definition at line 208 of file Machine.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 for binary problems
Reimplemented in CKernelMachine.
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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virtualinherited |
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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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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virtual |
classify data using ID3 Tree
data | data to be classified |
Reimplemented from CMachine.
Definition at line 49 of file ID3ClassifierTree.cpp.
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virtualinherited |
applies to one vector
Reimplemented in CKernelMachine, CRelaxedTree, COnlineLinearMachine, CLinearMachine, CKNN, CMulticlassMachine, CDistanceMachine, CScatterSVM, CGaussianNaiveBayes, and CPluginEstimate.
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virtualinherited |
apply machine to data in means of regression problem
Reimplemented in CKernelMachine, COnlineLinearMachine, CNeuralNetwork, CLinearMachine, CCHAIDTree, CStochasticGBMachine, CCARTree, 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 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 |
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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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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virtualinherited |
get classifier type
Reimplemented in CLaRank, CSVMLight, CNeuralNetwork, CCCSOSVM, CLeastAngleRegression, CLDA, CQDA, CLibLinearMTL, CBaggingMachine, CLibLinear, CGaussianProcessClassification, CKernelRidgeRegression, CLibSVR, CKNN, CGaussianNaiveBayes, CSVRLight, CMCLDA, CLinearRidgeRegression, CScatterSVM, CGaussianProcessRegression, CSGDQN, CSVMSGD, COnlineSVMSGD, CLeastSquaresRegression, CMKLRegression, CDomainAdaptationSVMLinear, CMKLMulticlass, CKMeansBase, CHierarchical, CMKLOneClass, CLibSVM, CStochasticSOSVM, CMKLClassification, CDomainAdaptationSVM, CLPBoost, CPerceptron, CAveragedPerceptron, CFWSOSVM, CNewtonSVM, CLPM, CGMNPSVM, CSVMLightOneClass, CSVMLin, CMulticlassLibSVM, CLibSVMOneClass, CMPDSVM, CGNPPSVM, and CCPLEXSVM.
Definition at line 92 of file Machine.cpp.
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inherited |
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inherited |
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inherited |
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virtualinherited |
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virtualinherited |
get problem type
Reimplemented from CMachine.
Reimplemented in CCHAIDTree, and CCARTree.
Definition at line 32 of file BaseMulticlassMachine.cpp.
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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 |
get name
Reimplemented from CTreeMachine< id3TreeNodeData >.
Definition at line 86 of file ID3ClassifierTree.h.
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inherited |
get number of machines
Definition at line 27 of file BaseMulticlassMachine.cpp.
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inherited |
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inherited |
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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 |
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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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virtualinherited |
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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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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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 459 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 454 of file SGObject.cpp.
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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.
bool prune_tree | ( | CDenseFeatures< float64_t > * | validation_data, |
CMulticlassLabels * | validation_labels, | ||
float64_t | epsilon = 0.f |
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) |
prune id3 decision tree - uses reduced error pruning algorithm
cf. http://en.wikipedia.org/wiki/Pruning_%28decision_trees%29#Reduced_error_pruning
At each node, starting from leaf nodes up to the root node, this algorithm checks if removing the subtree gives better results (or somewhat comparable results). If so, it replaces the subtree with a leaf node. The algorithm implemented is recursive which starts with the root node. At each node, it prunes its children first and then itself. As the algorithm goes down each level during recursion, it creates the new set of features by pushing subset into subset stack. While retracting, it pops these subsets to access previous state of feature matrix (see add_subset() and remove_subset() in Shogun documentation).
validation_data | feature vectors from validation dataset |
validation_labels | multiclass labels from validation dataset |
epsilon | prune subtree even if there is epsilon loss in accuracy |
Definition at line 60 of file ID3ClassifierTree.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 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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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 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 |
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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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 maximum training time
t | maximimum training time |
Definition at line 82 of file Machine.cpp.
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inherited |
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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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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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protectedvirtualinherited |
enable unlocked cross-validation - no model features to store
Reimplemented from CMachine.
Definition at line 152 of file TreeMachine.h.
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virtualinherited |
Reimplemented in CKernelMachine.
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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
NOT IMPLEMENTED
indices | index vector (of locked features) that is used for training |
Reimplemented in CKernelMachine.
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protectedvirtual |
train machine - build ID3 Tree from training data
data | training data |
Reimplemented from CMachine.
Definition at line 70 of file ID3ClassifierTree.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.
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inherited |
io
Definition at line 537 of file SGObject.h.
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protectedinherited |
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inherited |
parameters wrt which we can compute gradients
Definition at line 552 of file SGObject.h.
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inherited |
Hash of parameter values
Definition at line 555 of file SGObject.h.
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protectedinherited |
machines
Definition at line 56 of file BaseMulticlassMachine.h.
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protectedinherited |
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inherited |
model selection parameters
Definition at line 549 of file SGObject.h.
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inherited |
parameters
Definition at line 546 of file SGObject.h.
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protectedinherited |
tree root
Definition at line 156 of file TreeMachine.h.
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protectedinherited |
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protectedinherited |
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inherited |
parallel
Definition at line 540 of file SGObject.h.
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inherited |
version
Definition at line 543 of file SGObject.h.