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SHOGUN
4.1.0
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This class implements the stochastic gradient boosting algorithm for ensemble learning invented by Jerome H. Friedman. This class works with a variety of loss functions like squared loss, exponential loss, Huber loss etc which can be accessed through Shogun's CLossFunction interface (cf. http://www.shogun-toolbox.org/doc/en/latest/classshogun_1_1CLossFunction.html). Additionally, it can create an ensemble of any regressor class derived from the CMachine class (cf. http://www.shogun-toolbox.org/doc/en/latest/classshogun_1_1CMachine.html). For one dimensional optimization, this class uses the backtracking linesearch accessed via Shogun's L-BFGS class. A concise description of the algorithm implemented can be found in the following link : http://en.wikipedia.org/wiki/Gradient_boosting#Algorithm.
在文件 StochasticGBMachine.h 第 52 行定义.
Public 属性 | |
| SGIO * | io |
| Parallel * | parallel |
| Version * | version |
| Parameter * | m_parameters |
| Parameter * | m_model_selection_parameters |
| Parameter * | m_gradient_parameters |
| uint32_t | m_hash |
Protected 成员函数 | |
| virtual bool | train_machine (CFeatures *data=NULL) |
| float64_t | compute_multiplier (CRegressionLabels *f, CRegressionLabels *hm) |
| CMachine * | fit_model (CDenseFeatures< float64_t > *feats, CRegressionLabels *labels) |
| CRegressionLabels * | compute_pseudo_residuals (CRegressionLabels *inter_f) |
| void | apply_subset (CDenseFeatures< float64_t > *f, CLabels *interf) |
| void | initialize_learners () |
| float64_t | get_gamma (void *instance) |
| void | init () |
| virtual void | store_model_features () |
| virtual bool | is_label_valid (CLabels *lab) const |
| 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) |
静态 Protected 成员函数 | |
| static float64_t | lbfgs_evaluate (void *obj, const float64_t *parameters, float64_t *gradient, const int dim, const float64_t step) |
Protected 属性 | |
| CMachine * | m_machine |
| CLossFunction * | m_loss |
| int32_t | m_num_iter |
| float64_t | m_subset_frac |
| float64_t | m_learning_rate |
| CDynamicObjectArray * | m_weak_learners |
| CDynamicArray< float64_t > * | m_gamma |
| float64_t | m_max_train_time |
| CLabels * | m_labels |
| ESolverType | m_solver_type |
| bool | m_store_model_features |
| bool | m_data_locked |
| CStochasticGBMachine | ( | CMachine * | machine = NULL, |
| CLossFunction * | loss = NULL, |
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| int32_t | num_iterations = 100, |
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| float64_t | learning_rate = 1.0, |
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| float64_t | subset_fraction = 0.6 |
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| ) |
Constructor
| machine | The class of machine which will constitute the ensemble |
| loss | loss function |
| num_iterations | number of iterations of boosting |
| subset_fraction | fraction of trainining vectors to be chosen randomly w/o replacement |
| learning_rate | shrinkage factor |
在文件 StochasticGBMachine.cpp 第 37 行定义.
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virtual |
Destructor
在文件 StochasticGBMachine.cpp 第 60 行定义.
apply machine to data if data is not specified apply to the current features
| data | (test)data to be classified |
在文件 Machine.cpp 第 152 行定义.
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virtualinherited |
apply machine to data in means of binary classification problem
被 CKernelMachine, COnlineLinearMachine, CWDSVMOcas, CNeuralNetwork, CLinearMachine, CGaussianProcessClassification, CDomainAdaptationSVMLinear, CDomainAdaptationSVM, CPluginEstimate , 以及 CBaggingMachine 重载.
在文件 Machine.cpp 第 208 行定义.
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virtualinherited |
apply machine to data in means of latent problem
被 CLinearLatentMachine 重载.
在文件 Machine.cpp 第 232 行定义.
Applies a locked machine on a set of indices. Error if machine is not locked
| indices | index vector (of locked features) that is predicted |
在文件 Machine.cpp 第 187 行定义.
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virtualinherited |
applies a locked machine on a set of indices for binary problems
被 CKernelMachine , 以及 CMultitaskLinearMachine 重载.
在文件 Machine.cpp 第 238 行定义.
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virtualinherited |
applies a locked machine on a set of indices for latent problems
在文件 Machine.cpp 第 266 行定义.
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virtualinherited |
applies a locked machine on a set of indices for multiclass problems
在文件 Machine.cpp 第 252 行定义.
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virtualinherited |
applies a locked machine on a set of indices for regression problems
被 CKernelMachine 重载.
在文件 Machine.cpp 第 245 行定义.
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virtualinherited |
applies a locked machine on a set of indices for structured problems
在文件 Machine.cpp 第 259 行定义.
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virtualinherited |
apply machine to data in means of multiclass classification problem
被 CNeuralNetwork, CCHAIDTree, CCARTree, CGaussianProcessClassification, CMulticlassMachine, CKNN, CC45ClassifierTree, CID3ClassifierTree, CDistanceMachine, CVwConditionalProbabilityTree, CGaussianNaiveBayes, CConditionalProbabilityTree, CMCLDA, CQDA, CRelaxedTree , 以及 CBaggingMachine 重载.
在文件 Machine.cpp 第 220 行定义.
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virtualinherited |
applies to one vector
被 CKernelMachine, CRelaxedTree, CWDSVMOcas, COnlineLinearMachine, CLinearMachine, CMultitaskLinearMachine, CMulticlassMachine, CKNN, CDistanceMachine, CMultitaskLogisticRegression, CMultitaskLeastSquaresRegression, CScatterSVM, CGaussianNaiveBayes, CPluginEstimate , 以及 CFeatureBlockLogisticRegression 重载.
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virtual |
apply_regression
| data | test data |
重载 CMachine .
在文件 StochasticGBMachine.cpp 第 142 行定义.
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virtualinherited |
apply machine to data in means of SO classification problem
被 CLinearStructuredOutputMachine 重载.
在文件 Machine.cpp 第 226 行定义.
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protected |
add randomized subset to relevant parameters
| f | training data |
| interf | intermediate boosted model labels for training data |
在文件 StochasticGBMachine.cpp 第 275 行定义.
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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. |
在文件 SGObject.cpp 第 597 行定义.
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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.
在文件 SGObject.cpp 第 714 行定义.
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protected |
compute gamma values
| f | labels from the intermediate model |
| hm | labels from the newly trained base model |
在文件 StochasticGBMachine.cpp 第 229 行定义.
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protected |
compute pseudo_residuals
| inter_f | intermediate boosted model labels for training data |
在文件 StochasticGBMachine.cpp 第 262 行定义.
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 |
被 CKernelMachine 重载.
在文件 Machine.cpp 第 112 行定义.
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virtualinherited |
Unlocks a locked machine and restores previous state
被 CKernelMachine 重载.
在文件 Machine.cpp 第 143 行定义.
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virtualinherited |
A deep copy. All the instance variables will also be copied.
在文件 SGObject.cpp 第 198 行定义.
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) |
在文件 SGObject.cpp 第 618 行定义.
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protected |
train base model
| feats | training data |
| labels | training labels |
在文件 StochasticGBMachine.cpp 第 245 行定义.
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virtualinherited |
get classifier type
被 CLaRank, CSVMLight, CDualLibQPBMSOSVM, CNeuralNetwork, CCCSOSVM, CLeastAngleRegression, CLDA, CKernelRidgeRegression, CLibLinearMTL, CBaggingMachine, CLibLinear, CGaussianProcessClassification, CKMeans, CLibSVR, CQDA, CGaussianNaiveBayes, CSVRLight, CMCLDA, CLinearRidgeRegression, CKNN, CScatterSVM, CGaussianProcessRegression, CSGDQN, CSVMSGD, CSVMOcas, COnlineSVMSGD, CLeastSquaresRegression, CMKLRegression, CDomainAdaptationSVMLinear, CMKLMulticlass, CWDSVMOcas, CHierarchical, CMKLOneClass, CLibSVM, CStochasticSOSVM, CMKLClassification, CDomainAdaptationSVM, CLPBoost, CPerceptron, CAveragedPerceptron, CFWSOSVM, CNewtonSVM, CLPM, CGMNPSVM, CSVMLightOneClass, CSVMLin, CMulticlassLibSVM, CLibSVMOneClass, CMPDSVM, CGPBTSVM, CGNPPSVM , 以及 CCPLEXSVM 重载.
在文件 Machine.cpp 第 92 行定义.
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protected |
apply lbfgs to get gamma
| instance | stores parameters to be passed to lbfgs_evaluate |
在文件 StochasticGBMachine.cpp 第 301 行定义.
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inherited |
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inherited |
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inherited |
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virtualinherited |
| float64_t get_learning_rate | ( | ) | const |
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virtual |
| CMachine * get_machine | ( | ) | const |
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virtualinherited |
returns type of problem machine solves
被 CNeuralNetwork, CRandomForest, CCHAIDTree, CCARTree , 以及 CBaseMulticlassMachine 重载.
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inherited |
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inherited |
在文件 SGObject.cpp 第 498 行定义.
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inherited |
Returns description of a given parameter string, if it exists. SG_ERROR otherwise
| param_name | name of the parameter |
在文件 SGObject.cpp 第 522 行定义.
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inherited |
Returns index of model selection parameter with provided index
| param_name | name of model selection parameter |
在文件 SGObject.cpp 第 535 行定义.
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virtual |
| int32_t get_num_iterations | ( | ) | const |
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inherited |
| float64_t get_subset_fraction | ( | ) | const |
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protected |
initialize
在文件 StochasticGBMachine.cpp 第 385 行定义.
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protected |
reset arrays of weak learners and gamma values
在文件 StochasticGBMachine.cpp 第 290 行定义.
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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 |
在文件 SGObject.cpp 第 296 行定义.
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protectedvirtualinherited |
check whether the labels is valid.
Subclasses can override this to implement their check of label types.
| lab | the labels being checked, guaranteed to be non-NULL |
被 CNeuralNetwork, CCARTree, CCHAIDTree, CGaussianProcessRegression , 以及 CBaseMulticlassMachine 重载.
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staticprotected |
call-back evaluate method for lbfgs
| obj | object parameters required for loss calculation |
| parameters | current state of variables of target function |
| gradient | stores gradient computed by this method |
| dim | dimensions |
| step | step in linesearch |
在文件 StochasticGBMachine.cpp 第 313 行定义.
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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 |
在文件 SGObject.cpp 第 369 行定义.
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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. |
被 CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel , 以及 CExponentialKernel 重载.
在文件 SGObject.cpp 第 426 行定义.
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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. |
被 CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.
在文件 SGObject.cpp 第 421 行定义.
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virtualinherited |
在文件 SGObject.cpp 第 262 行定义.
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inherited |
prints all parameter registered for model selection and their type
在文件 SGObject.cpp 第 474 行定义.
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virtualinherited |
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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 |
在文件 SGObject.cpp 第 314 行定义.
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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. |
被 CKernel 重载.
在文件 SGObject.cpp 第 436 行定义.
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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. |
被 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.cpp 第 431 行定义.
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inherited |
在文件 SGObject.cpp 第 41 行定义.
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inherited |
在文件 SGObject.cpp 第 46 行定义.
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inherited |
在文件 SGObject.cpp 第 51 行定义.
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inherited |
在文件 SGObject.cpp 第 56 行定义.
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inherited |
在文件 SGObject.cpp 第 61 行定义.
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inherited |
在文件 SGObject.cpp 第 66 行定义.
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inherited |
在文件 SGObject.cpp 第 71 行定义.
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inherited |
在文件 SGObject.cpp 第 76 行定义.
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inherited |
在文件 SGObject.cpp 第 81 行定义.
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inherited |
在文件 SGObject.cpp 第 86 行定义.
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inherited |
在文件 SGObject.cpp 第 91 行定义.
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inherited |
在文件 SGObject.cpp 第 96 行定义.
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inherited |
在文件 SGObject.cpp 第 101 行定义.
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inherited |
在文件 SGObject.cpp 第 106 行定义.
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inherited |
在文件 SGObject.cpp 第 111 行定义.
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inherited |
set generic type to T
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inherited |
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inherited |
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inherited |
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virtualinherited |
set labels
| lab | labels |
被 CNeuralNetwork, CGaussianProcessMachine, CCARTree, CStructuredOutputMachine, CRelaxedTree , 以及 CMulticlassMachine 重载.
在文件 Machine.cpp 第 65 行定义.
| void set_learning_rate | ( | float64_t | lr | ) |
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virtual |
| void set_machine | ( | CMachine * | machine | ) |
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inherited |
| void set_num_iterations | ( | int32_t | iter | ) |
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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 |
在文件 Machine.cpp 第 107 行定义.
| void set_subset_fraction | ( | float64_t | frac | ) |
set subset fraction
| frac | subset fraction (should lie between 0 and 1) |
在文件 StochasticGBMachine.cpp 第 118 行定义.
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virtualinherited |
A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.
被 CGaussianKernel 重载.
在文件 SGObject.cpp 第 192 行定义.
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protectedvirtualinherited |
Stores feature data of underlying model. After this method has been called, it is possible to change the machine's feature data and call apply(), which is then performed on the training feature data that is part of the machine's model.
Base method, has to be implemented in order to allow cross-validation and model selection.
NOT IMPLEMENTED! Has to be done in subclasses
被 CKernelMachine, CKNN, CLinearMulticlassMachine, CTreeMachine< T >, CTreeMachine< ConditionalProbabilityTreeNodeData >, CTreeMachine< RelaxedTreeNodeData >, CTreeMachine< id3TreeNodeData >, CTreeMachine< VwConditionalProbabilityTreeNodeData >, CTreeMachine< CARTreeNodeData >, CTreeMachine< C45TreeNodeData >, CTreeMachine< CHAIDTreeNodeData >, CTreeMachine< NbodyTreeNodeData >, CLinearMachine, CGaussianProcessMachine, CHierarchical, CDistanceMachine, CKernelMulticlassMachine , 以及 CLinearStructuredOutputMachine 重载.
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virtualinherited |
被 CKernelMachine , 以及 CMultitaskLinearMachine 重载.
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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. |
被 CRelaxedTree, CAutoencoder, CSGDQN , 以及 COnlineSVMSGD 重载.
在文件 Machine.cpp 第 39 行定义.
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 |
被 CKernelMachine , 以及 CMultitaskLinearMachine 重载.
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protectedvirtual |
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protectedvirtualinherited |
returns whether machine require labels for training
被 COnlineLinearMachine, CHierarchical, CLinearLatentMachine, CVwConditionalProbabilityTree, CConditionalProbabilityTree , 以及 CLibSVMOneClass 重载.
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inherited |
unset generic type
this has to be called in classes specializing a template class
在文件 SGObject.cpp 第 303 行定义.
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virtualinherited |
Updates the hash of current parameter combination
在文件 SGObject.cpp 第 248 行定义.
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inherited |
io
在文件 SGObject.h 第 369 行定义.
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protected |
gamma - weak learner weights
在文件 StochasticGBMachine.h 第 223 行定义.
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inherited |
parameters wrt which we can compute gradients
在文件 SGObject.h 第 384 行定义.
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inherited |
Hash of parameter values
在文件 SGObject.h 第 387 行定义.
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protected |
learning_rate
在文件 StochasticGBMachine.h 第 217 行定义.
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protected |
loss function
在文件 StochasticGBMachine.h 第 208 行定义.
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protected |
machine to be used for GBoosting
在文件 StochasticGBMachine.h 第 205 行定义.
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model selection parameters
在文件 SGObject.h 第 381 行定义.
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protected |
num of iterations
在文件 StochasticGBMachine.h 第 211 行定义.
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inherited |
parameters
在文件 SGObject.h 第 378 行定义.
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protectedinherited |
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protectedinherited |
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protected |
subset fraction
在文件 StochasticGBMachine.h 第 214 行定义.
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protected |
array of weak learners
在文件 StochasticGBMachine.h 第 220 行定义.
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parallel
在文件 SGObject.h 第 372 行定义.
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inherited |
version
在文件 SGObject.h 第 375 行定义.
