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SHOGUN
4.1.0
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Class LibSVR, performs support vector regression using LibSVM.
The SVR solution can be expressed as
\[ f({\bf x})=\sum_{i=1}^{N} \alpha_i k({\bf x}, {\bf x_i})+b \]
where \(\alpha\) and \(b\) are determined in training, i.e. using a pre-specified kernel, a given tube-epsilon for the epsilon insensitive loss, the follwoing quadratic problem is minimized (using sequential minimal decomposition (SMO))
\begin{eqnarray*} \max_{{\bf \alpha},{\bf \alpha}^*} &-\frac{1}{2}\sum_{i,j=1}^N(\alpha_i-\alpha_i^*)(\alpha_j-\alpha_j^*){\bf x}_i^T {\bf x}_j -\sum_{i=1}^N(\alpha_i+\alpha_i^*)\epsilon - \sum_{i=1}^N(\alpha_i-\alpha_i^*)y_i\\ \mbox{wrt}:& {\bf \alpha},{\bf \alpha}^*\in{\bf R}^N\\ \mbox{s.t.}:& 0\leq \alpha_i,\alpha_i^*\leq C,\, \forall i=1\dots N\\ &\sum_{i=1}^N(\alpha_i-\alpha_i^*)y_i=0 \end{eqnarray*}
Note that the SV regression problem is reduced to the standard SV classification problem by introducing artificial labels \(-y_i\) which leads to the epsilon insensitive loss constraints *
\begin{eqnarray*} {\bf w}^T{\bf x}_i+b-c_i-\xi_i\leq 0,&\, \forall i=1\dots N\\ -{\bf w}^T{\bf x}_i-b-c_i^*-\xi_i^*\leq 0,&\, \forall i=1\dots N \end{eqnarray*}
with \(c_i=y_i+ \epsilon\) and \(c_i^*=-y_i+ \epsilon\)
This class also support the \(\nu\)-SVR regression version of the problem, where \(\nu\) replaces the \(\epsilon\) parameter and represents an upper bound on the fraction of margin errors and a lower bound on the fraction of support vectors. While it is easier to interpret, the resulting optimization problem usually takes longer to solve. Note that these different parameters do not result in different predictive power. For a given problem, the best SVR for each parametrization will lead to the same results. See the letter "Training \f$\nu\f$-Support Vector Regression: Theory and Algorithms" by Chih-Chung Chang and Chih-Jen Lin for the relation of \(\epsilon\)-SVR and \(\nu\)-SVR.
静态 Public 成员函数 | |
| static void * | apply_helper (void *p) |
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) |
| virtual float64_t * | get_linear_term_array () |
| SGVector< float64_t > | apply_get_outputs (CFeatures *data) |
| 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) |
Protected 属性 | |
| svm_problem | problem |
| svm_parameter | param |
| struct svm_model * | model |
| LIBSVR_SOLVER_TYPE | solver_type |
| SGVector< float64_t > | m_linear_term |
| bool | svm_loaded |
| float64_t | epsilon |
| float64_t | tube_epsilon |
| float64_t | nu |
| float64_t | C1 |
| float64_t | C2 |
| float64_t | objective |
| int32_t | qpsize |
| bool | use_shrinking |
| bool(* | callback )(CMKL *mkl, const float64_t *sumw, const float64_t suma) |
| CMKL * | mkl |
| CKernel * | kernel |
| CCustomKernel * | m_custom_kernel |
| CKernel * | m_kernel_backup |
| bool | use_batch_computation |
| bool | use_linadd |
| bool | use_bias |
| float64_t | m_bias |
| SGVector< float64_t > | m_alpha |
| SGVector< int32_t > | m_svs |
| float64_t | m_max_train_time |
| CLabels * | m_labels |
| ESolverType | m_solver_type |
| bool | m_store_model_features |
| bool | m_data_locked |
| CLibSVR | ( | ) |
default constructor, creates a EPISOLON-SVR
在文件 LibSVR.cpp 第 18 行定义.
| CLibSVR | ( | float64_t | C, |
| float64_t | svr_param, | ||
| CKernel * | k, | ||
| CLabels * | lab, | ||
| LIBSVR_SOLVER_TYPE | st = LIBSVR_EPSILON_SVR |
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| ) |
constructor
| C | constant C |
| svr_param | tube epsilon or SVR-NU depending on solver type |
| k | kernel |
| lab | labels |
| st | solver type to use, EPSILON-SVR or NU-SVR |
在文件 LibSVR.cpp 第 25 行定义.
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virtual |
在文件 LibSVR.cpp 第 51 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 kernel machine to data for binary classification task
| data | (test)data to be classified |
重载 CMachine .
被 CDomainAdaptationSVM 重载.
在文件 KernelMachine.cpp 第 248 行定义.
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staticinherited |
apply example helper, used in threads
| p | params of the thread |
在文件 KernelMachine.cpp 第 424 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. Error if machine is not locked. Binary case
| indices | index vector (of locked features) that is predicted |
重载 CMachine .
在文件 KernelMachine.cpp 第 518 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 KernelMachine.cpp 第 531 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. Error if machine is not locked. Binary case
| indices | index vector (of locked features) that is predicted |
重载 CMachine .
在文件 KernelMachine.cpp 第 524 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 |
apply kernel machine to one example
| num | which example to apply to |
重载 CMachine .
在文件 KernelMachine.cpp 第 405 行定义.
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virtualinherited |
apply kernel machine to data for regression task
| data | (test)data to be classified |
重载 CMachine .
在文件 KernelMachine.cpp 第 242 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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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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create new model
| num | number of alphas and support vectors in new model |
在文件 KernelMachine.cpp 第 194 行定义.
Locks the machine on given labels and data. After this call, only train_locked and apply_locked may be called.
Computes kernel matrix to speed up train/apply calls
| labs | labels used for locking |
| features | features used for locking |
重载 CMachine .
在文件 KernelMachine.cpp 第 623 行定义.
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virtualinherited |
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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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inherited |
在文件 KernelMachine.cpp 第 189 行定义.
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inherited |
check if batch computation is enabled
在文件 KernelMachine.cpp 第 99 行定义.
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virtual |
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protectedvirtualinherited |
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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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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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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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get support vector at given index
| idx | index of support vector |
在文件 KernelMachine.cpp 第 134 行定义.
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inherited |
在文件 KernelMachine.cpp 第 184 行定义.
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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 |
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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inherited |
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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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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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inherited |
problem type
| MACHINE_PROBLEM_TYPE | ( | PT_REGRESSION | ) |
problem type
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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 |
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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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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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 |
set alpha at given index to given value
| idx | index of alpha vector |
| val | new value of alpha vector |
在文件 KernelMachine.cpp 第 159 行定义.
set alphas to given values
| alphas | float vector with all alphas to set |
在文件 KernelMachine.cpp 第 174 行定义.
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inherited |
set batch computation enabled
| enable | if batch computation shall be enabled |
在文件 KernelMachine.cpp 第 94 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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在文件 SGObject.cpp 第 66 行定义.
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在文件 SGObject.cpp 第 71 行定义.
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在文件 SGObject.cpp 第 76 行定义.
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在文件 SGObject.cpp 第 81 行定义.
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在文件 SGObject.cpp 第 86 行定义.
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在文件 SGObject.cpp 第 91 行定义.
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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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在文件 SGObject.cpp 第 106 行定义.
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在文件 SGObject.cpp 第 111 行定义.
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set generic type to T
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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.
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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.
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set support vector at given index to given value
| idx | index of support vector |
| val | new value of support vector |
在文件 KernelMachine.cpp 第 149 行定义.
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inherited |
set support vectors to given values
| svs | integer vector with all support vectors indexes to set |
在文件 KernelMachine.cpp 第 179 行定义.
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inherited |
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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 the SV indices and sets it to the lhs of the underlying kernel. Then, all SV indices are set to identity.
May be overwritten by subclasses in case the model should be stored differently.
重载 CMachine .
在文件 KernelMachine.cpp 第 453 行定义.
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virtualinherited |
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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
| indices | index vector (of locked features) that is used for training |
重载 CMachine .
在文件 KernelMachine.cpp 第 482 行定义.
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protectedvirtual |
train regression
| data | training data (parameter can be avoided if distance or kernel-based regressor are used and distance/kernels are initialized with train data) |
重载 CMachine .
在文件 LibSVR.cpp 第 61 行定义.
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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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io
在文件 SGObject.h 第 369 行定义.
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protectedinherited |
kernel
在文件 KernelMachine.h 第 311 行定义.
coefficients alpha
在文件 KernelMachine.h 第 332 行定义.
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protectedinherited |
bias term b
在文件 KernelMachine.h 第 329 行定义.
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protectedinherited |
is filled with pre-computed custom kernel on data lock
在文件 KernelMachine.h 第 314 行定义.
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parameters wrt which we can compute gradients
在文件 SGObject.h 第 384 行定义.
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Hash of parameter values
在文件 SGObject.h 第 387 行定义.
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protectedinherited |
old kernel is stored here on data lock
在文件 KernelMachine.h 第 317 行定义.
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model selection parameters
在文件 SGObject.h 第 381 行定义.
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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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protectedinherited |
array of ``support vectors'' (indices of feature objects)
在文件 KernelMachine.h 第 335 行定义.
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protectedinherited |
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parallel
在文件 SGObject.h 第 372 行定义.
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protectedinherited |
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protectedinherited |
if batch computation is enabled
在文件 KernelMachine.h 第 320 行定义.
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protectedinherited |
if bias shall be used
在文件 KernelMachine.h 第 326 行定义.
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protectedinherited |
if linadd is enabled
在文件 KernelMachine.h 第 323 行定义.
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version
在文件 SGObject.h 第 375 行定义.
