SHOGUN  3.2.1
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CRandomCARTree类 参考

详细描述

This class implements randomized CART algorithm used in the tree growing process of candidate trees in Random Forests algorithm. The tree growing process is different from the original CART algorithm because of the input attributes which are considered for each node split. In randomized CART, a few (fixed number) attributes are randomly chosen from all available attributes while deciding the best split. This is unlike the original CART where all available attributes are considered while deciding the best split.

在文件 RandomCARTree.h48 行定义.

类 CRandomCARTree 继承关系图:
Inheritance graph
[图例]

Public 类型

typedef CTreeMachineNode
< CARTreeNodeData
node_t
 
typedef CBinaryTreeMachineNode
< CARTreeNodeData
bnode_t
 

Public 成员函数

 CRandomCARTree ()
 
virtual ~CRandomCARTree ()
 
virtual const char * get_name () const
 
void set_feature_subset_size (int32_t size)
 
int32_t get_feature_subset_size () const
 
virtual void set_labels (CLabels *lab)
 
virtual EProblemType get_machine_problem_type () const
 
void set_machine_problem_type (EProblemType mode)
 
virtual bool is_label_valid (CLabels *lab) const
 
virtual CMulticlassLabelsapply_multiclass (CFeatures *data=NULL)
 
virtual CRegressionLabelsapply_regression (CFeatures *data=NULL)
 
void prune_using_test_dataset (CDenseFeatures< float64_t > *feats, CLabels *gnd_truth, SGVector< float64_t > weights=SGVector< float64_t >())
 
void set_weights (SGVector< float64_t > w)
 
SGVector< float64_tget_weights () const
 
void clear_weights ()
 
void set_feature_types (SGVector< bool > ft)
 
SGVector< bool > get_feature_types () const
 
void clear_feature_types ()
 
int32_t get_num_folds () const
 
void set_num_folds (int32_t folds)
 
int32_t get_max_depth () const
 
void set_max_depth (int32_t depth)
 
int32_t get_min_node_size () const
 
void set_min_node_size (int32_t nsize)
 
void set_cv_pruning ()
 
void unset_cv_pruning ()
 
float64_t get_label_epsilon ()
 
void set_label_epsilon (float64_t epsilon)
 
void set_root (CTreeMachineNode< CARTreeNodeData > *root)
 
CTreeMachineNode
< CARTreeNodeData > * 
get_root ()
 
CTreeMachineclone_tree ()
 
int32_t get_num_machines () const
 
virtual bool train (CFeatures *data=NULL)
 
virtual CLabelsapply (CFeatures *data=NULL)
 
virtual CBinaryLabelsapply_binary (CFeatures *data=NULL)
 
virtual CStructuredLabelsapply_structured (CFeatures *data=NULL)
 
virtual CLatentLabelsapply_latent (CFeatures *data=NULL)
 
virtual CLabelsget_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 CLabelsapply_locked (SGVector< index_t > indices)
 
virtual CBinaryLabelsapply_locked_binary (SGVector< index_t > indices)
 
virtual CRegressionLabelsapply_locked_regression (SGVector< index_t > indices)
 
virtual CMulticlassLabelsapply_locked_multiclass (SGVector< index_t > indices)
 
virtual CStructuredLabelsapply_locked_structured (SGVector< index_t > indices)
 
virtual CLatentLabelsapply_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 CSGObjectshallow_copy () const
 
virtual CSGObjectdeep_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="", int32_t param_version=Version::get_version_parameter())
 
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
 
DynArray< TParameter * > * load_file_parameters (const SGParamInfo *param_info, int32_t file_version, CSerializableFile *file, const char *prefix="")
 
DynArray< TParameter * > * load_all_file_parameters (int32_t file_version, int32_t current_version, CSerializableFile *file, const char *prefix="")
 
void map_parameters (DynArray< TParameter * > *param_base, int32_t &base_version, DynArray< const SGParamInfo * > *target_param_infos)
 
void set_global_io (SGIO *io)
 
SGIOget_global_io ()
 
void set_global_parallel (Parallel *parallel)
 
Parallelget_global_parallel ()
 
void set_global_version (Version *version)
 
Versionget_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)
 
virtual void update_parameter_hash ()
 
virtual bool parameter_hash_changed ()
 
virtual bool equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)
 
virtual CSGObjectclone ()
 

Public 属性

SGIOio
 
Parallelparallel
 
Versionversion
 
Parameterm_parameters
 
Parameterm_model_selection_parameters
 
Parameterm_gradient_parameters
 
ParameterMapm_parameter_map
 
uint32_t m_hash
 

静态 Public 属性

static const float64_t MISSING =CMath::MAX_REAL_NUMBER
 
static const float64_t MIN_SPLIT_GAIN =1e-7
 
static const float64_t EQ_DELTA =1e-7
 

Protected 成员函数

virtual int32_t compute_best_attribute (SGMatrix< float64_t > mat, SGVector< float64_t > weights, SGVector< float64_t > labels_vec, SGVector< float64_t > left, SGVector< float64_t > right, SGVector< bool > is_left_final, int32_t &num_missing, int32_t &count_left, int32_t &count_right)
 
virtual bool train_machine (CFeatures *data=NULL)
 
virtual CBinaryTreeMachineNode
< CARTreeNodeData > * 
CARTtrain (CFeatures *data, SGVector< float64_t > weights, CLabels *labels, int32_t level)
 
SGVector< float64_tget_unique_labels (SGVector< float64_t > labels_vec, int32_t &n_ulabels)
 
SGVector< bool > surrogate_split (SGMatrix< float64_t > data, SGVector< float64_t > weights, SGVector< bool > nm_left, int32_t attr)
 
void handle_missing_vecs_for_continuous_surrogate (SGMatrix< float64_t > m, CDynamicArray< int32_t > *missing_vecs, CDynamicArray< float64_t > *association_index, CDynamicArray< int32_t > *intersect_vecs, SGVector< bool > is_left, SGVector< float64_t > weights, float64_t p, int32_t attr)
 
void handle_missing_vecs_for_nominal_surrogate (SGMatrix< float64_t > m, CDynamicArray< int32_t > *missing_vecs, CDynamicArray< float64_t > *association_index, CDynamicArray< int32_t > *intersect_vecs, SGVector< bool > is_left, SGVector< float64_t > weights, float64_t p, int32_t attr)
 
float64_t gain (SGVector< float64_t > wleft, SGVector< float64_t > wright, SGVector< float64_t > wtotal, SGVector< float64_t > labels)
 
float64_t gain (SGVector< float64_t > wleft, SGVector< float64_t > wright, SGVector< float64_t > wtotal)
 
float64_t gini_impurity_index (SGVector< float64_t > weighted_lab_classes, float64_t &total_weight)
 
float64_t least_squares_deviation (SGVector< float64_t > labels, SGVector< float64_t > weights, float64_t &total_weight)
 
CLabelsapply_from_current_node (CDenseFeatures< float64_t > *feats, bnode_t *current)
 
void prune_by_cross_validation (CDenseFeatures< float64_t > *data, int32_t folds)
 
float64_t compute_error (CLabels *labels, CLabels *reference, SGVector< float64_t > weights)
 
CDynamicObjectArrayprune_tree (CTreeMachine< CARTreeNodeData > *tree)
 
float64_t find_weakest_alpha (bnode_t *node)
 
void cut_weakest_link (bnode_t *node, float64_t alpha)
 
void form_t1 (bnode_t *node)
 
virtual void store_model_features ()
 
virtual bool train_require_labels () const
 
virtual TParametermigrate (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)
 

Protected 属性

float64_t m_label_epsilon
 
SGVector< bool > m_nominal
 
SGVector< float64_tm_weights
 
bool m_types_set
 
bool m_weights_set
 
bool m_apply_cv_pruning
 
int32_t m_folds
 
EProblemType m_mode
 
CDynamicArray< float64_t > * m_alphas
 
int32_t m_max_depth
 
int32_t m_min_node_size
 
CTreeMachineNode
< CARTreeNodeData > * 
m_root
 
CDynamicObjectArraym_machines
 
float64_t m_max_train_time
 
CLabelsm_labels
 
ESolverType m_solver_type
 
bool m_store_model_features
 
bool m_data_locked
 

成员类型定义说明

bnode_t type- Tree node with max 2 possible children

在文件 TreeMachine.h55 行定义.

node_t type- Tree node with many possible children

在文件 TreeMachine.h52 行定义.

构造及析构函数说明

constructor

在文件 RandomCARTree.cpp36 行定义.

~CRandomCARTree ( )
virtual

destructor

在文件 RandomCARTree.cpp42 行定义.

成员函数说明

CLabels * apply ( CFeatures data = NULL)
virtualinherited

apply machine to data if data is not specified apply to the current features

参数
data(test)data to be classified
返回
classified labels

在文件 Machine.cpp160 行定义.

CBinaryLabels * apply_binary ( CFeatures data = NULL)
virtualinherited

apply machine to data in means of binary classification problem

CKernelMachine, COnlineLinearMachine, CWDSVMOcas, CNeuralNetwork, CLinearMachine, CDomainAdaptationSVMLinear, CPluginEstimate, CGaussianProcessBinaryClassification , 以及 CBaggingMachine 重载.

在文件 Machine.cpp216 行定义.

CLabels * apply_from_current_node ( CDenseFeatures< float64_t > *  feats,
bnode_t current 
)
protectedinherited

uses current subtree to classify/regress data

参数
featsdata to be classified/regressed
currentroot of current subtree
返回
classification/regression labels of input data

在文件 CARTree.cpp976 行定义.

CLatentLabels * apply_latent ( CFeatures data = NULL)
virtualinherited

apply machine to data in means of latent problem

CLinearLatentMachine 重载.

在文件 Machine.cpp240 行定义.

CLabels * apply_locked ( SGVector< index_t indices)
virtualinherited

Applies a locked machine on a set of indices. Error if machine is not locked

参数
indicesindex vector (of locked features) that is predicted

在文件 Machine.cpp195 行定义.

CBinaryLabels * apply_locked_binary ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for binary problems

CKernelMachine , 以及 CMultitaskLinearMachine 重载.

在文件 Machine.cpp246 行定义.

CLatentLabels * apply_locked_latent ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for latent problems

在文件 Machine.cpp274 行定义.

CMulticlassLabels * apply_locked_multiclass ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for multiclass problems

在文件 Machine.cpp260 行定义.

CRegressionLabels * apply_locked_regression ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for regression problems

CKernelMachine 重载.

在文件 Machine.cpp253 行定义.

CStructuredLabels * apply_locked_structured ( SGVector< index_t indices)
virtualinherited

applies a locked machine on a set of indices for structured problems

在文件 Machine.cpp267 行定义.

CMulticlassLabels * apply_multiclass ( CFeatures data = NULL)
virtualinherited

classify data using Classification Tree

参数
datadata to be classified
返回
MulticlassLabels corresponding to labels of various test vectors

重载 CMachine .

在文件 CARTree.cpp99 行定义.

virtual float64_t apply_one ( int32_t  i)
virtualinherited
CRegressionLabels * apply_regression ( CFeatures data = NULL)
virtualinherited

Get regression labels using Regression Tree

参数
datadata whose regression output is needed
返回
Regression output for various test vectors

重载 CMachine .

在文件 CARTree.cpp111 行定义.

CStructuredLabels * apply_structured ( CFeatures data = NULL)
virtualinherited

apply machine to data in means of SO classification problem

CLinearStructuredOutputMachine 重载.

在文件 Machine.cpp234 行定义.

void build_gradient_parameter_dictionary ( CMap< TParameter *, CSGObject * > *  dict)
inherited

Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.

参数
dictdictionary of parameters to be built.

在文件 SGObject.cpp1185 行定义.

CBinaryTreeMachineNode< CARTreeNodeData > * CARTtrain ( CFeatures data,
SGVector< float64_t weights,
CLabels labels,
int32_t  level 
)
protectedvirtualinherited

CARTtrain - recursive CART training method

参数
datatraining data
weightsvector of weights of data points
labelslabels of data points
levelcurrent tree depth
返回
pointer to the root of the CART subtree

在文件 CARTree.cpp285 行定义.

void clear_feature_types ( )
inherited

clear feature types of various features

在文件 CARTree.cpp197 行定义.

void clear_weights ( )
inherited

clear weights of data points

在文件 CARTree.cpp180 行定义.

CSGObject * clone ( )
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.

返回
an identical copy of the given object, which is disjoint in memory. NULL if the clone fails. Note that the returned object is SG_REF'ed

在文件 SGObject.cpp1302 行定义.

CTreeMachine* clone_tree ( )
inherited

clone tree

返回
clone of entire tree

在文件 TreeMachine.h97 行定义.

int32_t compute_best_attribute ( SGMatrix< float64_t mat,
SGVector< float64_t weights,
SGVector< float64_t labels_vec,
SGVector< float64_t left,
SGVector< float64_t right,
SGVector< bool >  is_left_final,
int32_t &  num_missing,
int32_t &  count_left,
int32_t &  count_right 
)
protectedvirtual

computes best attribute for CARTtrain

参数
matdata matrix
weightsdata weights
labels_vecdata labels
leftstores feature values for left transition
rightstores feature values for right transition
is_left_finalstores which feature vectors go to the left child
num_missingnumber of missing attributes
count_leftstores number of feature values for left transition
count_rightstores number of feature values for right transition
返回
index to the best attribute

重载 CCARTree .

在文件 RandomCARTree.cpp52 行定义.

float64_t compute_error ( CLabels labels,
CLabels reference,
SGVector< float64_t weights 
)
protectedinherited

computes error in classification/regression for classification it eveluates weight_missclassified/total_weight for regression it evaluates weighted sum of squared error/total_weight

参数
labelsthe labels whose error needs to be calculated
referenceactual labels against which test labels are compared
weightsweights associated with the labels
返回
error evaluated

在文件 CARTree.cpp1198 行定义.

void cut_weakest_link ( bnode_t node,
float64_t  alpha 
)
protectedinherited

recursively cuts weakest link(s) in a tree

参数
nodethe root of subtree whose weakest link it cuts
alphaalpha value corresponding to weakest link

在文件 CARTree.cpp1305 行定义.

void data_lock ( CLabels labs,
CFeatures features 
)
virtualinherited

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

参数
labslabels used for locking
featuresfeatures used for locking

CKernelMachine 重载.

在文件 Machine.cpp120 行定义.

void data_unlock ( )
virtualinherited

Unlocks a locked machine and restores previous state

CKernelMachine 重载.

在文件 Machine.cpp151 行定义.

CSGObject * deep_copy ( ) const
virtualinherited

A deep copy. All the instance variables will also be copied.

在文件 SGObject.cpp146 行定义.

bool equals ( CSGObject other,
float64_t  accuracy = 0.0,
bool  tolerant = false 
)
virtualinherited

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.

参数
otherobject to compare with
accuracyaccuracy to use for comparison (optional)
tolerantallows linient check on float equality (within accuracy)
返回
true if all parameters were equal, false if not

在文件 SGObject.cpp1206 行定义.

float64_t find_weakest_alpha ( bnode_t node)
protectedinherited

recursively finds alpha corresponding to weakest link(s)

参数
nodethe root of subtree whose weakest link it finds
返回
alpha value corresponding to the weakest link in subtree

在文件 CARTree.cpp1284 行定义.

void form_t1 ( bnode_t node)
protectedinherited

recursively forms base case $ft_1$f tree from $ft_max$f during pruning

参数
nodethe root of current subtree

在文件 CARTree.cpp1335 行定义.

float64_t gain ( SGVector< float64_t wleft,
SGVector< float64_t wright,
SGVector< float64_t wtotal,
SGVector< float64_t labels 
)
protectedinherited

returns gain in regression case

参数
wleftleft child weight distribution
wrightright child weights distribution
wtotalweight distribution in current node
labelsregression labels
返回
least squared deviation gain achieved after spliting the node

在文件 CARTree.cpp918 行定义.

float64_t gain ( SGVector< float64_t wleft,
SGVector< float64_t wright,
SGVector< float64_t wtotal 
)
protectedinherited

returns gain in Gini impurity measure

参数
wleftleft child label distribution
wrightright child label distribution
wtotallabel distribution in current node
返回
Gini gain achieved after spliting the node

在文件 CARTree.cpp932 行定义.

EMachineType get_classifier_type ( )
virtualinherited
int32_t get_feature_subset_size ( ) const

get number of random features to choose in each node split

返回
size subset size

在文件 RandomCARTree.h72 行定义.

SGVector< bool > get_feature_types ( ) const
inherited

set feature types of various features

返回
bool vector - true for nominal feature false for continuous feature type

在文件 CARTree.cpp192 行定义.

SGIO * get_global_io ( )
inherited

get the io object

返回
io object

在文件 SGObject.cpp183 行定义.

Parallel * get_global_parallel ( )
inherited

get the parallel object

返回
parallel object

在文件 SGObject.cpp224 行定义.

Version * get_global_version ( )
inherited

get the version object

返回
version object

在文件 SGObject.cpp237 行定义.

float64_t get_label_epsilon ( )
inherited

get label epsilon

返回
equality range for regression labels

在文件 CARTree.h220 行定义.

CLabels * get_labels ( )
virtualinherited

get labels

返回
labels

在文件 Machine.cpp84 行定义.

virtual EProblemType get_machine_problem_type ( ) const
virtualinherited

get problem type - multiclass classification or regression

返回
PT_MULTICLASS or PT_REGRESSION

重载 CBaseMulticlassMachine .

在文件 CARTree.h115 行定义.

int32_t get_max_depth ( ) const
inherited

get max allowed tree depth

返回
max allowed tree depth

在文件 CARTree.cpp214 行定义.

float64_t get_max_train_time ( )
inherited

get maximum training time

返回
maximum training time

在文件 Machine.cpp95 行定义.

int32_t get_min_node_size ( ) const
inherited

get min allowed node size

返回
min allowed node size

在文件 CARTree.cpp225 行定义.

SGStringList< char > get_modelsel_names ( )
inherited
返回
vector of names of all parameters which are registered for model selection

在文件 SGObject.cpp1077 行定义.

char * get_modsel_param_descr ( const char *  param_name)
inherited

Returns description of a given parameter string, if it exists. SG_ERROR otherwise

参数
param_namename of the parameter
返回
description of the parameter

在文件 SGObject.cpp1101 行定义.

index_t get_modsel_param_index ( const char *  param_name)
inherited

Returns index of model selection parameter with provided index

参数
param_namename of model selection parameter
返回
index of model selection parameter with provided name, -1 if there is no such

在文件 SGObject.cpp1114 行定义.

virtual const char* get_name ( ) const
virtual

get name

返回
class name CARTree

重载 CCARTree .

在文件 RandomCARTree.h60 行定义.

int32_t get_num_folds ( ) const
inherited

get number of subsets used for cross validation

返回
number of folds used in cross validation

在文件 CARTree.cpp203 行定义.

int32_t get_num_machines ( ) const
inherited

get number of machines

返回
number of machines

在文件 BaseMulticlassMachine.cpp27 行定义.

CTreeMachineNode<CARTreeNodeData >* get_root ( )
inherited

get root

返回
root the root node of the tree

在文件 TreeMachine.h88 行定义.

ESolverType get_solver_type ( )
inherited

get solver type

返回
solver

在文件 Machine.cpp110 行定义.

SGVector< float64_t > get_unique_labels ( SGVector< float64_t labels_vec,
int32_t &  n_ulabels 
)
protectedinherited

modify labels for compute_best_attribute

参数
labels_veclabels vector
n_ulabelsstores number of unique labels
返回
unique labels

在文件 CARTree.cpp462 行定义.

SGVector< float64_t > get_weights ( ) const
inherited

get weights of data points

返回
vector of weights

在文件 CARTree.cpp175 行定义.

float64_t gini_impurity_index ( SGVector< float64_t weighted_lab_classes,
float64_t total_weight 
)
protectedinherited

returns Gini impurity of a node

参数
weighted_lab_classesvector of weights associated with various labels
total_weightstores the total weight of all classes
返回
Gini index of the node

在文件 CARTree.cpp944 行定义.

void handle_missing_vecs_for_continuous_surrogate ( SGMatrix< float64_t m,
CDynamicArray< int32_t > *  missing_vecs,
CDynamicArray< float64_t > *  association_index,
CDynamicArray< int32_t > *  intersect_vecs,
SGVector< bool >  is_left,
SGVector< float64_t weights,
float64_t  p,
int32_t  attr 
)
protectedinherited

handles missing values for a chosen continuous surrogate attribute

参数
mtraining data matrix
missing_vecscolumn indices of vectors with missing attribute in data matrix
association_indexstores the final lambda values used to address members of missing_vecs
intersect_vecscolumn indices of vectors with known values for the best attribute as well as the chosen surrogate
is_leftwhether a vector goes into left child
weightsweights of training data vectors
pmin(p_l,p_r) in the lambda formula
attrsurrogate attribute chosen for split
返回
vector denoting whether a data point goes to left child for all data points including ones with missing attributes

在文件 CARTree.cpp781 行定义.

void handle_missing_vecs_for_nominal_surrogate ( SGMatrix< float64_t m,
CDynamicArray< int32_t > *  missing_vecs,
CDynamicArray< float64_t > *  association_index,
CDynamicArray< int32_t > *  intersect_vecs,
SGVector< bool >  is_left,
SGVector< float64_t weights,
float64_t  p,
int32_t  attr 
)
protectedinherited

handles missing values for a chosen nominal surrogate attribute

参数
mtraining data matrix
missing_vecscolumn indices of vectors with missing attribute in data matrix
association_indexstores the final lambda values used to address members of missing_vecs
intersect_vecscolumn indices of vectors with known values for the best attribute as well as the chosen surrogate
is_leftwhether a vector goes into left child
weightsweights of training data vectors
pmin(p_l,p_r) in the lambda formula
attrsurrogate attribute chosen for split
返回
vector denoting whether a data point goes to left child for all data points including ones with missing attributes

在文件 CARTree.cpp838 行定义.

bool is_data_locked ( ) const
inherited
返回
whether this machine is locked

在文件 Machine.h292 行定义.

bool is_generic ( EPrimitiveType *  generic) const
virtualinherited

If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.

参数
genericset to the type of the generic if returning TRUE
返回
TRUE if a class template.

在文件 SGObject.cpp243 行定义.

bool is_label_valid ( CLabels lab) const
virtualinherited

whether labels supplied are valid for current problem type

参数
lablabels supplied
返回
true for valid labels, false for invalid labels

重载 CBaseMulticlassMachine .

在文件 CARTree.cpp89 行定义.

float64_t least_squares_deviation ( SGVector< float64_t labels,
SGVector< float64_t weights,
float64_t total_weight 
)
protectedinherited

returns least squares deviation

参数
labelsregression labels
weightsweights of regression data points
total_weightstores sum of weights in weights vector
返回
least squares deviation of the data

在文件 CARTree.cpp958 行定义.

DynArray< TParameter * > * load_all_file_parameters ( int32_t  file_version,
int32_t  current_version,
CSerializableFile file,
const char *  prefix = "" 
)
inherited

maps all parameters of this instance to the provided file version and loads all parameter data from the file into an array, which is sorted (basically calls load_file_parameter(...) for all parameters and puts all results into a sorted array)

参数
file_versionparameter version of the file
current_versionversion from which mapping begins (you want to use Version::get_version_parameter() for this in most cases)
filefile to load from
prefixprefix for members
返回
(sorted) array of created TParameter instances with file data

在文件 SGObject.cpp648 行定义.

DynArray< TParameter * > * load_file_parameters ( const SGParamInfo param_info,
int32_t  file_version,
CSerializableFile file,
const char *  prefix = "" 
)
inherited

loads some specified parameters from a file with a specified version The provided parameter info has a version which is recursively mapped until the file parameter version is reached. Note that there may be possibly multiple parameters in the mapping, therefore, a set of TParameter instances is returned

参数
param_infoinformation of parameter
file_versionparameter version of the file, must be <= provided parameter version
filefile to load from
prefixprefix for members
返回
new array with TParameter instances with the attached data

在文件 SGObject.cpp489 行定义.

bool load_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 
)
virtualinherited

Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!

参数
filewhere to load from
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
返回
TRUE if done, otherwise FALSE

在文件 SGObject.cpp320 行定义.

void load_serializable_post ( )
throw (ShogunException
)
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.

异常
ShogunExceptionWill be thrown if an error occurres.

CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel , 以及 CExponentialKernel 重载.

在文件 SGObject.cpp1004 行定义.

void load_serializable_pre ( )
throw (ShogunException
)
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.

异常
ShogunExceptionWill be thrown if an error occurres.

CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.

在文件 SGObject.cpp999 行定义.

void map_parameters ( DynArray< TParameter * > *  param_base,
int32_t &  base_version,
DynArray< const SGParamInfo * > *  target_param_infos 
)
inherited

Takes a set of TParameter instances (base) with a certain version and a set of target parameter infos and recursively maps the base level wise to the current version using CSGObject::migrate(...). The base is replaced. After this call, the base version containing parameters should be of same version/type as the initial target parameter infos. Note for this to work, the migrate methods and all the internal parameter mappings have to match

参数
param_baseset of TParameter instances that are mapped to the provided target parameter infos
base_versionversion of the parameter base
target_param_infosset of SGParamInfo instances that specify the target parameter base

在文件 SGObject.cpp686 行定义.

TParameter * migrate ( DynArray< TParameter * > *  param_base,
const SGParamInfo target 
)
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

参数
param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
返回
a new TParameter instance with migrated data from the base of the type which is specified by the target parameter

在文件 SGObject.cpp893 行定义.

void one_to_one_migration_prepare ( DynArray< TParameter * > *  param_base,
const SGParamInfo target,
TParameter *&  replacement,
TParameter *&  to_migrate,
char *  old_name = NULL 
)
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)

参数
param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
replacement(used as output) here the TParameter instance which is returned by migration is created into
to_migratethe only source that is used for migration
old_namewith this parameter, a name change may be specified

在文件 SGObject.cpp833 行定义.

bool parameter_hash_changed ( )
virtualinherited
返回
whether parameter combination has changed since last update

在文件 SGObject.cpp209 行定义.

virtual void post_lock ( CLabels labs,
CFeatures features 
)
virtualinherited

post lock

CMultitaskLinearMachine 重载.

在文件 Machine.h283 行定义.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

在文件 SGObject.cpp1053 行定义.

void print_serializable ( const char *  prefix = "")
virtualinherited

prints registered parameters out

参数
prefixprefix for members

在文件 SGObject.cpp255 行定义.

void prune_by_cross_validation ( CDenseFeatures< float64_t > *  data,
int32_t  folds 
)
protectedinherited

prune by cross validation

参数
datatraining data
foldsthe integer V for V-fold cross validation

在文件 CARTree.cpp1059 行定义.

CDynamicObjectArray * prune_tree ( CTreeMachine< CARTreeNodeData > *  tree)
protectedinherited

cost-complexity pruning

参数
treethe tree to be pruned
返回
CDynamicObjectArray of pruned trees

在文件 CARTree.cpp1236 行定义.

void prune_using_test_dataset ( CDenseFeatures< float64_t > *  feats,
CLabels gnd_truth,
SGVector< float64_t weights = SGVector<float64_t>() 
)
inherited

uses test dataset to choose best pruned subtree

参数
featstest data to be used
gnd_truthtest labels
weightsweights of data points

在文件 CARTree.cpp123 行定义.

bool save_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 
)
virtualinherited

Save this object to file.

参数
filewhere to save the object; will be closed during returning if PREFIX is an empty string.
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
返回
TRUE if done, otherwise FALSE

在文件 SGObject.cpp261 行定义.

void save_serializable_post ( )
throw (ShogunException
)
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.

异常
ShogunExceptionWill be thrown if an error occurres.

CKernel 重载.

在文件 SGObject.cpp1014 行定义.

void save_serializable_pre ( )
throw (ShogunException
)
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.

异常
ShogunExceptionWill be thrown if an error occurres.

CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.

在文件 SGObject.cpp1009 行定义.

void set_cv_pruning ( )
inherited

apply cross validation pruning

在文件 CARTree.h211 行定义.

void set_feature_subset_size ( int32_t  size)

set number of random features to choose in each node split

参数
sizesubset size

在文件 RandomCARTree.cpp46 行定义.

void set_feature_types ( SGVector< bool >  ft)
inherited

set feature types of various features

参数
ftbool vector true for nominal feature false for continuous feature type

在文件 CARTree.cpp186 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp38 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp43 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp48 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp53 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp58 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp63 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp68 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp73 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp78 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp83 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp88 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp93 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp98 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp103 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp108 行定义.

void set_generic ( )
inherited

set generic type to T

void set_global_io ( SGIO io)
inherited

set the io object

参数
ioio object to use

在文件 SGObject.cpp176 行定义.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

参数
parallelparallel object to use

在文件 SGObject.cpp189 行定义.

void set_global_version ( Version version)
inherited

set the version object

参数
versionversion object to use

在文件 SGObject.cpp230 行定义.

void set_label_epsilon ( float64_t  epsilon)
inherited

set label epsilon

参数
epsilonequality range for regression labels

在文件 CARTree.cpp236 行定义.

void set_labels ( CLabels lab)
virtualinherited

set labels - automagically switch machine problem type based on type of labels supplied

参数
lablabels

重载 CMachine .

在文件 CARTree.cpp70 行定义.

void set_machine_problem_type ( EProblemType  mode)
inherited

set problem type - multiclass classification or regression

参数
modeEProblemType PT_MULTICLASS or PT_REGRESSION

在文件 CARTree.cpp84 行定义.

void set_max_depth ( int32_t  depth)
inherited

set max allowed tree depth

参数
depthmax allowed tree depth

在文件 CARTree.cpp219 行定义.

void set_max_train_time ( float64_t  t)
inherited

set maximum training time

参数
tmaximimum training time

在文件 Machine.cpp90 行定义.

void set_min_node_size ( int32_t  nsize)
inherited

set min allowed node size

参数
minallowed node size

在文件 CARTree.cpp230 行定义.

void set_num_folds ( int32_t  folds)
inherited

set number of subsets for cross validation

参数
foldsnumber of folds used in cross validation

在文件 CARTree.cpp208 行定义.

void set_root ( CTreeMachineNode< CARTreeNodeData > *  root)
inherited

set root

参数
rootthe root node of the tree

在文件 TreeMachine.h78 行定义.

void set_solver_type ( ESolverType  st)
inherited

set solver type

参数
stsolver type

在文件 Machine.cpp105 行定义.

void set_store_model_features ( bool  store_model)
virtualinherited

Setter for store-model-features-after-training flag

参数
store_modelwhether model should be stored after training

在文件 Machine.cpp115 行定义.

void set_weights ( SGVector< float64_t w)
inherited

set weights of data points

参数
wvector of weights

在文件 CARTree.cpp169 行定义.

CSGObject * shallow_copy ( ) const
virtualinherited

A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.

CGaussianKernel 重载.

在文件 SGObject.cpp140 行定义.

virtual void store_model_features ( )
protectedvirtualinherited

enable unlocked cross-validation - no model features to store

重载 CMachine .

在文件 TreeMachine.h152 行定义.

virtual bool supports_locking ( ) const
virtualinherited
返回
whether this machine supports locking

CKernelMachine , 以及 CMultitaskLinearMachine 重载.

在文件 Machine.h289 行定义.

SGVector< bool > surrogate_split ( SGMatrix< float64_t data,
SGVector< float64_t weights,
SGVector< bool >  nm_left,
int32_t  attr 
)
protectedinherited

handles missing values through surrogate splits

参数
datatraining data matrix
weightsvector of weights of data points
nm_leftwhether a data point is put into left child (available for only data points with non-missing attribute attr)
attrbest attribute chosen for split
返回
vector denoting whether a data point goes to left child for all data points including ones with missing attributes

在文件 CARTree.cpp706 行定义.

bool train ( CFeatures data = NULL)
virtualinherited

train machine

参数
datatraining 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.
返回
whether training was successful

CRelaxedTree, CAutoencoder, CSGDQN , 以及 COnlineSVMSGD 重载.

在文件 Machine.cpp47 行定义.

virtual bool train_locked ( SGVector< index_t indices)
virtualinherited

Trains a locked machine on a set of indices. Error if machine is not locked

NOT IMPLEMENTED

参数
indicesindex vector (of locked features) that is used for training
返回
whether training was successful

CKernelMachine , 以及 CMultitaskLinearMachine 重载.

在文件 Machine.h235 行定义.

bool train_machine ( CFeatures data = NULL)
protectedvirtualinherited

train machine - build CART from training data

参数
datatraining data
返回
true

重载 CMachine .

在文件 CARTree.cpp242 行定义.

virtual bool train_require_labels ( ) const
protectedvirtualinherited

returns whether machine require labels for training

COnlineLinearMachine, CHierarchical, CLinearLatentMachine, CVwConditionalProbabilityTree, CConditionalProbabilityTree , 以及 CLibSVMOneClass 重载.

在文件 Machine.h350 行定义.

void unset_cv_pruning ( )
inherited

do not apply cross validation pruning

在文件 CARTree.h214 行定义.

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

在文件 SGObject.cpp250 行定义.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

在文件 SGObject.cpp196 行定义.

类成员变量说明

const float64_t EQ_DELTA =1e-7
staticinherited

equality epsilon

在文件 CARTree.h415 行定义.

SGIO* io
inherited

io

在文件 SGObject.h461 行定义.

CDynamicArray<float64_t>* m_alphas
protectedinherited

stores \(\alpha_k\) values evaluated in cost-complexity pruning

在文件 CARTree.h443 行定义.

bool m_apply_cv_pruning
protectedinherited

flag indicating whether cross validation pruning has to be applied or not - false by default

在文件 CARTree.h434 行定义.

bool m_data_locked
protectedinherited

whether data is locked

在文件 Machine.h366 行定义.

int32_t m_folds
protectedinherited

V in V-fold cross validation - 5 by default

在文件 CARTree.h437 行定义.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

在文件 SGObject.h476 行定义.

uint32_t m_hash
inherited

Hash of parameter values

在文件 SGObject.h482 行定义.

float64_t m_label_epsilon
protectedinherited

equality range for regression labels

在文件 CARTree.h419 行定义.

CLabels* m_labels
protectedinherited

labels

在文件 Machine.h357 行定义.

CDynamicObjectArray* m_machines
protectedinherited

machines

在文件 BaseMulticlassMachine.h56 行定义.

int32_t m_max_depth
protectedinherited

max allowed depth of tree

在文件 CARTree.h446 行定义.

float64_t m_max_train_time
protectedinherited

maximum training time

在文件 Machine.h354 行定义.

int32_t m_min_node_size
protectedinherited

minimum number of feature vectors required in a node

在文件 CARTree.h449 行定义.

EProblemType m_mode
protectedinherited

Problem type : PT_MULTICLASS or PT_REGRESSION

在文件 CARTree.h440 行定义.

Parameter* m_model_selection_parameters
inherited

model selection parameters

在文件 SGObject.h473 行定义.

SGVector<bool> m_nominal
protectedinherited

vector depicting whether various feature dimensions are nominal or not

在文件 CARTree.h422 行定义.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

在文件 SGObject.h479 行定义.

Parameter* m_parameters
inherited

parameters

在文件 SGObject.h470 行定义.

CTreeMachineNode<CARTreeNodeData >* m_root
protectedinherited

tree root

在文件 TreeMachine.h156 行定义.

ESolverType m_solver_type
protectedinherited

solver type

在文件 Machine.h360 行定义.

bool m_store_model_features
protectedinherited

whether model features should be stored after training

在文件 Machine.h363 行定义.

bool m_types_set
protectedinherited

flag storing whether the type of various feature dimensions are specified using is_nominal_feature

在文件 CARTree.h428 行定义.

SGVector<float64_t> m_weights
protectedinherited

weights of samples in training set

在文件 CARTree.h425 行定义.

bool m_weights_set
protectedinherited

flag storing whether weights of samples are specified using weights vector

在文件 CARTree.h431 行定义.

const float64_t MIN_SPLIT_GAIN =1e-7
staticinherited

min gain for splitting to be allowed

在文件 CARTree.h412 行定义.

const float64_t MISSING =CMath::MAX_REAL_NUMBER
staticinherited

denotes that a feature in a vector is missing MISSING = NOT_A_NUMBER

在文件 CARTree.h409 行定义.

Parallel* parallel
inherited

parallel

在文件 SGObject.h464 行定义.

Version* version
inherited

version

在文件 SGObject.h467 行定义.


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