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SHOGUN
4.2.0
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SHOGUN
4.2.0
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This class implements the CHAID algorithm proposed by Kass (1980) for decision tree learning. CHAID consists of three steps: merging, splitting and stopping. A tree is grown by repeatedly using these three steps on each node starting from the root node. CHAID accepts nominal or ordinal categorical predictors only. If predictors are continuous, they have to be transformed into ordinal predictors before tree growing.
CONVERTING CONTINUOUS PREDICTORS TO ORDINAL :
Continuous predictors are converted to ordinal by binning. The number of bins (K) has to be supplied by the user. Given K, a predictor is split in such a way that all the bins get the same number (more or less) of distinct predictor values. The maximum feature value in each bin is used as a breakpoint.
MERGING :
During the merging step, allowable pairs of categories of a predictor are evaluated for similarity. If the similarity of a pair is above a threshold, the categories constituting the pair are merged into a single category. The process is repeated until there is no pair left having high similarity between its categories. Similarity between categories is evaluated using the p_value
SPLITTING :
The splitting step selects which predictor to be used to best split the node. Selection is accomplished by comparing the adjusted p_value associated with each predictor. The predictor that has the smallest adjusted p_value is chosen for splitting the node.
STOPPING :
The tree growing process stops if any of the following conditions is satisfied :
.
Definition at line 90 of file CHAIDTree.h.
Public Types | |
| typedef CTreeMachineNode < CHAIDTreeNodeData > | node_t |
| typedef CBinaryTreeMachineNode < CHAIDTreeNodeData > | bnode_t |
Public Member Functions | |
| CCHAIDTree () | |
| CCHAIDTree (int32_t dependent_vartype) | |
| CCHAIDTree (int32_t dependent_vartype, SGVector< int32_t > feature_types, int32_t num_breakpoints=0) | |
| virtual | ~CCHAIDTree () |
| virtual const char * | get_name () const |
| virtual EProblemType | get_machine_problem_type () const |
| virtual bool | is_label_valid (CLabels *lab) const |
| virtual CMulticlassLabels * | apply_multiclass (CFeatures *data=NULL) |
| virtual CRegressionLabels * | apply_regression (CFeatures *data=NULL) |
| void | set_weights (SGVector< float64_t > w) |
| SGVector< float64_t > | get_weights () const |
| void | clear_weights () |
| void | set_feature_types (SGVector< int32_t > ft) |
| SGVector< int32_t > | get_feature_types () const |
| void | clear_feature_types () |
| void | set_dependent_vartype (int32_t var) |
| int32_t | get_dependent_vartype () const |
| void | set_max_tree_depth (int32_t d) |
| int32_t | get_specified_max_tree_depth () const |
| void | set_min_node_size (int32_t size) |
| int32_t | get_min_node_size () const |
| void | set_alpha_merge (float64_t a) |
| float64_t | get_alpha_merge () const |
| void | set_alpha_split (float64_t a) |
| float64_t | get_alpha_split () const |
| void | set_num_breakpoints (int32_t b) |
| float64_t | get_num_breakpoints () const |
| void | set_root (CTreeMachineNode< CHAIDTreeNodeData > *root) |
| CTreeMachineNode < CHAIDTreeNodeData > * | get_root () |
| CTreeMachine * | clone_tree () |
| int32_t | get_num_machines () const |
| virtual bool | train (CFeatures *data=NULL) |
| virtual CLabels * | apply (CFeatures *data=NULL) |
| virtual CBinaryLabels * | apply_binary (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 |
Static Public Attributes | |
| static const float64_t | MISSING =CMath::MAX_REAL_NUMBER |
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 < CHAIDTreeNodeData > * | 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.
| CCHAIDTree | ( | ) |
default constructor
Definition at line 39 of file CHAIDTree.cpp.
| CCHAIDTree | ( | int32_t | dependent_vartype | ) |
constructor
| dependent_vartype | feature type for dependent variable (0-nominal, 1-ordinal or 2-continuous) |
Definition at line 45 of file CHAIDTree.cpp.
| CCHAIDTree | ( | int32_t | dependent_vartype, |
| SGVector< int32_t > | feature_types, | ||
| int32_t | num_breakpoints = 0 |
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| ) |
constructor
| dependent_vartype | feature type for dependent variable (0-nominal, 1-ordinal or 2-continuous) |
| feature_types | type of various attributes (0-nominal, 1-ordinal or 2-continuous) |
| num_breakpoints | number of breakpoints for continuous to ordinal conversion of attributes |
Definition at line 52 of file CHAIDTree.cpp.
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virtual |
destructor
Definition at line 61 of file CHAIDTree.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 Classification Tree NOTE : This method replaces all values of continuous attributes in supplied data with the actual breakpoint values used for classification
| data | data to be classified |
Reimplemented from CMachine.
Definition at line 99 of file CHAIDTree.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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virtual |
Get regression labels using Regression Tree NOTE : This method replaces all values of continuous attributes in supplied data with the actual breakpoint values used for classification
| data | data whose regression output is needed |
Reimplemented from CMachine.
Definition at line 106 of file CHAIDTree.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.
| void clear_feature_types | ( | ) |
clear feature types of various features
Definition at line 143 of file CHAIDTree.cpp.
| void clear_weights | ( | ) |
clear weights of data points
Definition at line 127 of file CHAIDTree.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.
| float64_t get_alpha_merge | ( | ) | const |
| float64_t get_alpha_split | ( | ) | const |
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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.
| int32_t get_dependent_vartype | ( | ) | const |
get dependent variable type : 0 for nominal, 1 for ordinal and 2 for continuous
Definition at line 177 of file CHAIDTree.h.
| SGVector< int32_t > get_feature_types | ( | ) | const |
get feature types of various features
Definition at line 138 of file CHAIDTree.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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virtual |
get problem type - multiclass classification or regression
Reimplemented from CBaseMulticlassMachine.
Definition at line 65 of file CHAIDTree.cpp.
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| int32_t get_min_node_size | ( | ) | const |
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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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get name
Reimplemented from CTreeMachine< CHAIDTreeNodeData >.
Definition at line 114 of file CHAIDTree.h.
| float64_t get_num_breakpoints | ( | ) | const |
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get number of machines
Definition at line 27 of file BaseMulticlassMachine.cpp.
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| int32_t get_specified_max_tree_depth | ( | ) | const |
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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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virtual |
whether labels supplied are valid for current problem type
| lab | labels supplied |
Reimplemented from CBaseMulticlassMachine.
Definition at line 82 of file CHAIDTree.cpp.
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virtualinherited |
Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!
| file | where to load from |
| prefix | prefix for members |
Definition at line 402 of file SGObject.cpp.
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Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_POST is called.
| ShogunException | will be thrown if an error occurs. |
Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.
Definition at line 459 of file SGObject.cpp.
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Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_PRE is called.
| ShogunException | will be thrown if an error occurs. |
Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.
Definition at line 454 of file SGObject.cpp.
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Definition at line 295 of file SGObject.cpp.
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inherited |
prints all parameter registered for model selection and their type
Definition at line 507 of file SGObject.cpp.
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virtualinherited |
prints registered parameters out
| prefix | prefix for members |
Definition at line 341 of file SGObject.cpp.
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protectedinherited |
Registers a class parameter which is identified by a tag. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.
| _tag | name and type information of parameter |
| value | value of the parameter |
Definition at line 439 of file SGObject.h.
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protectedinherited |
Registers a class parameter which is identified by a name. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.
| name | name of the parameter |
| value | value of the parameter along with type information |
Definition at line 452 of file SGObject.h.
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Save this object to file.
| file | where to save the object; will be closed during returning if PREFIX is an empty string. |
| prefix | prefix for members |
Definition at line 347 of file SGObject.cpp.
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Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_POST is called.
| ShogunException | will be thrown if an error occurs. |
Reimplemented in CKernel.
Definition at line 469 of file SGObject.cpp.
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protectedvirtualinherited | |||||||||||||
Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_PRE is called.
| ShogunException | will be thrown if an error occurs. |
Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.
Definition at line 464 of file SGObject.cpp.
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inherited |
Setter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.
| _tag | name and type information of parameter |
| value | value of the parameter |
Definition at line 328 of file SGObject.h.
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inherited |
Setter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.
| name | name of the parameter |
| value | value of the parameter along with type information |
Definition at line 354 of file SGObject.h.
| void set_alpha_merge | ( | float64_t | a | ) |
| void set_alpha_split | ( | float64_t | a | ) |
| void set_dependent_vartype | ( | int32_t | var | ) |
set dependent variable type : 0 for nominal, 1 for ordinal and 2 for continuous
| var | integer corresponding to the dependent variable type |
Definition at line 148 of file CHAIDTree.cpp.
| void set_feature_types | ( | SGVector< int32_t > | ft | ) |
set feature types of various features
| ft | vector with feature types : 0-nominal, 1-ordinal or 2-continuous |
Definition at line 133 of file CHAIDTree.cpp.
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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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Definition at line 114 of file SGObject.cpp.
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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.
| void set_max_tree_depth | ( | int32_t | d | ) |
| void set_min_node_size | ( | int32_t | size | ) |
| void set_num_breakpoints | ( | int32_t | b | ) |
set number of breakpoints
| b | number of breakpoints |
Definition at line 222 of file CHAIDTree.h.
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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.
set weights of data points
| w | vector of weights |
Definition at line 113 of file CHAIDTree.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 CHAID from training data
| data | training data |
Reimplemented from CMachine.
Definition at line 154 of file CHAIDTree.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 |
|
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 |
|
protectedinherited |
|
static |
denotes that a feature in a vector is missing MISSING = MAX_REAL_NUMBER
Definition at line 393 of file CHAIDTree.h.
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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.