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SHOGUN
v3.2.0
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The Fully Independent Conditional Training inference method class.
This inference method computes the Cholesky and Alpha vectors approximately with the help of latent variables. For more details, see "Sparse Gaussian Process using Pseudo-inputs", Edward Snelson, Zoubin Ghahramani, NIPS 18, MIT Press, 2005.
This specific implementation was inspired by the infFITC.m file in the GPML toolbox.
NOTE: The Gaussian Likelihood Function must be used for this inference method.
在文件 FITCInferenceMethod.h 第 40 行定义.
静态 Public 成员函数 | |
| static CFITCInferenceMethod * | obtain_from_generic (CInferenceMethod *inference) |
Public 属性 | |
| SGIO * | io |
| Parallel * | parallel |
| Version * | version |
| Parameter * | m_parameters |
| Parameter * | m_model_selection_parameters |
| Parameter * | m_gradient_parameters |
| ParameterMap * | m_parameter_map |
| uint32_t | m_hash |
Protected 成员函数 | |
| virtual void | check_members () const |
| virtual void | update_alpha () |
| virtual void | update_chol () |
| virtual void | update_train_kernel () |
| virtual void | update_deriv () |
| virtual SGVector< float64_t > | get_derivative_wrt_inference_method (const TParameter *param) |
| virtual SGVector< float64_t > | get_derivative_wrt_likelihood_model (const TParameter *param) |
| virtual SGVector< float64_t > | get_derivative_wrt_kernel (const TParameter *param) |
| virtual SGVector< float64_t > | get_derivative_wrt_mean (const TParameter *param) |
| virtual TParameter * | migrate (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) |
静态 Protected 成员函数 | |
| static void * | get_derivative_helper (void *p) |
Protected 属性 | |
| CKernel * | m_kernel |
| CMeanFunction * | m_mean |
| CLikelihoodModel * | m_model |
| CFeatures * | m_features |
| CLabels * | m_labels |
| SGVector< float64_t > | m_alpha |
| SGMatrix< float64_t > | m_L |
| float64_t | m_scale |
| SGMatrix< float64_t > | m_ktrtr |
default constructor
在文件 FITCInferenceMethod.cpp 第 27 行定义.
| CFITCInferenceMethod | ( | CKernel * | kernel, |
| CFeatures * | features, | ||
| CMeanFunction * | mean, | ||
| CLabels * | labels, | ||
| CLikelihoodModel * | model, | ||
| CFeatures * | latent_features | ||
| ) |
constructor
| kernel | covariance function |
| features | features to use in inference |
| mean | mean function |
| labels | labels of the features |
| model | likelihood model to use |
| latent_features | features to use |
在文件 FITCInferenceMethod.cpp 第 32 行定义.
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virtual |
在文件 FITCInferenceMethod.cpp 第 49 行定义.
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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 1156 行定义.
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protectedvirtual |
check if members of object are valid for inference
重载 CInferenceMethod .
在文件 FITCInferenceMethod.cpp 第 74 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 1273 行定义.
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virtualinherited |
A deep copy. All the instance variables will also be copied.
在文件 SGObject.h 第 126 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) |
在文件 SGObject.cpp 第 1177 行定义.
get alpha vector
\[ \mu = K\alpha \]
where \(\mu\) is the mean and \(K\) is the prior covariance matrix.
实现了 CInferenceMethod.
在文件 FITCInferenceMethod.cpp 第 125 行定义.
get Cholesky decomposition matrix
\[ L = Cholesky(sW*K*sW+I) \]
where \(K\) is the prior covariance matrix, \(sW\) is the vector returned by get_diagonal_vector(), and \(I\) is the identity matrix.
实现了 CInferenceMethod.
在文件 FITCInferenceMethod.cpp 第 134 行定义.
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staticprotectedinherited |
pthread helper method to compute negative log marginal likelihood derivatives wrt hyperparameter
在文件 InferenceMethod.cpp 第 209 行定义.
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protectedvirtual |
returns derivative of negative log marginal likelihood wrt parameter of CInferenceMethod class
| param | parameter of CInferenceMethod class |
实现了 CInferenceMethod.
在文件 FITCInferenceMethod.cpp 第 323 行定义.
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protectedvirtual |
returns derivative of negative log marginal likelihood wrt kernel's parameter
| param | parameter of given kernel |
实现了 CInferenceMethod.
在文件 FITCInferenceMethod.cpp 第 406 行定义.
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protectedvirtual |
returns derivative of negative log marginal likelihood wrt parameter of likelihood model
| param | parameter of given likelihood model |
实现了 CInferenceMethod.
在文件 FITCInferenceMethod.cpp 第 371 行定义.
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protectedvirtual |
returns derivative of negative log marginal likelihood wrt mean function's parameter
| param | parameter of given mean function |
实现了 CInferenceMethod.
在文件 FITCInferenceMethod.cpp 第 488 行定义.
get diagonal vector
\[ Cov = (K^{-1}+sW^{2})^{-1} \]
where \(Cov\) is the posterior covariance matrix, \(K\) is the prior covariance matrix, and \(sW\) is the diagonal vector.
实现了 CInferenceMethod.
在文件 FITCInferenceMethod.cpp 第 87 行定义.
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virtualinherited |
get the gradient
| parameters | parameter's dictionary |
在文件 InferenceMethod.h 第 220 行定义.
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return what type of inference we are
重载 CInferenceMethod .
在文件 FITCInferenceMethod.h 第 65 行定义.
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Computes an unbiased estimate of the log-marginal-likelihood,
\[ log(p(y|X,\theta)), \]
where \(y\) are the labels, \(X\) are the features (omitted from in the following expressions), and \(\theta\) represent hyperparameters.
This is done via an approximation to the posterior \(q(f|y, \theta)\approx p(f|y, \theta)\), which is computed by the underlying CInferenceMethod instance (if implemented, otherwise error), and then using an importance sample estimator
\[ p(y|\theta)=\int p(y|f)p(f|\theta)df =\int p(y|f)\frac{p(f|\theta)}{q(f|y, \theta)}q(f|y, \theta)df \approx\frac{1}{n}\sum_{i=1}^n p(y|f^{(i)})\frac{p(f^{(i)}|\theta)} {q(f^{(i)}|y, \theta)}, \]
where \( f^{(i)} \) are samples from the posterior approximation \( q(f|y, \theta) \). The resulting estimator has a low variance if \( q(f|y, \theta) \) is a good approximation. It has large variance otherwise (while still being consistent).
| num_importance_samples | the number of importance samples \(n\) from \( q(f|y, \theta) \). |
| ridge_size | scalar that is added to the diagonal of the involved Gaussian distribution's covariance of GP prior and posterior approximation to stabilise things. Increase if Cholesky factorization fails. |
在文件 InferenceMethod.cpp 第 79 行定义.
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在文件 SGObject.cpp 第 1060 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 1084 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 1097 行定义.
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returns the name of the inference method
实现了 CSGObject.
在文件 FITCInferenceMethod.h 第 71 行定义.
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get negative log marginal likelihood
\[ -log(p(y|X, \theta)) \]
where \(y\) are the labels, \(X\) are the features, and \(\theta\) represent hyperparameters.
实现了 CInferenceMethod.
在文件 FITCInferenceMethod.cpp 第 104 行定义.
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get log marginal likelihood gradient
\[ -\frac{\partial log(p(y|X, \theta))}{\partial \theta} \]
where \(y\) are the labels, \(X\) are the features, and \(\theta\) represent hyperparameters.
在文件 InferenceMethod.cpp 第 138 行定义.
returns covariance matrix \(\Sigma\) of the Gaussian distribution \(\mathcal{N}(\mu,\Sigma)\), which is an approximation to the posterior:
\[ p(f|y) \approx q(f|y) = \mathcal{N}(\mu,\Sigma) \]
in case if particular inference method doesn't compute posterior \(p(f|y)\) exactly, and it returns covariance matrix \(\Sigma\) of the posterior Gaussian distribution \(\mathcal{N}(\mu,\Sigma)\) otherwise.
实现了 CInferenceMethod.
在文件 FITCInferenceMethod.cpp 第 149 行定义.
returns mean vector \(\mu\) of the Gaussian distribution \(\mathcal{N}(\mu,\Sigma)\), which is an approximation to the posterior:
\[ p(f|y) \approx q(f|y) = \mathcal{N}(\mu,\Sigma) \]
in case if particular inference method doesn't compute posterior \(p(f|y)\) exactly, and it returns covariance matrix \(\Sigma\) of the posterior Gaussian distribution \(\mathcal{N}(\mu,\Sigma)\) otherwise.
实现了 CInferenceMethod.
在文件 FITCInferenceMethod.cpp 第 143 行定义.
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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 228 行定义.
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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)
| file_version | parameter version of the file |
| current_version | version from which mapping begins (you want to use Version::get_version_parameter() for this in most cases) |
| file | file to load from |
| prefix | prefix for members |
在文件 SGObject.cpp 第 633 行定义.
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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
| param_info | information of parameter |
| file_version | parameter version of the file, must be <= provided parameter version |
| file | file to load from |
| prefix | prefix for members |
在文件 SGObject.cpp 第 474 行定义.
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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 |
| param_version | (optional) a parameter version different to (this is mainly for testing, better do not use) |
在文件 SGObject.cpp 第 305 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::LOAD_SERIALIZABLE_POST is called.
| ShogunException | Will be thrown if an error occurres. |
被 CWeightedDegreePositionStringKernel, CKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel , 以及 CExponentialKernel 重载.
在文件 SGObject.cpp 第 989 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 occurres. |
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 984 行定义.
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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
| param_base | set of TParameter instances that are mapped to the provided target parameter infos |
| base_version | version of the parameter base |
| target_param_infos | set of SGParamInfo instances that specify the target parameter base |
在文件 SGObject.cpp 第 671 行定义.
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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
| param_base | set of TParameter instances to use for migration |
| target | parameter info for the resulting TParameter |
在文件 SGObject.cpp 第 878 行定义.
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helper method used to specialize a base class instance
| inference | inference method |
在文件 FITCInferenceMethod.cpp 第 54 行定义.
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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)
| param_base | set of TParameter instances to use for migration |
| target | parameter info for the resulting TParameter |
| replacement | (used as output) here the TParameter instance which is returned by migration is created into |
| to_migrate | the only source that is used for migration |
| old_name | with this parameter, a name change may be specified |
在文件 SGObject.cpp 第 818 行定义.
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prints all parameter registered for model selection and their type
在文件 SGObject.cpp 第 1036 行定义.
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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 |
| param_version | (optional) a parameter version different to (this is mainly for testing, better do not use) |
在文件 SGObject.cpp 第 246 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 occurres. |
被 CKernel 重载.
在文件 SGObject.cpp 第 999 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 occurres. |
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 994 行定义.
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在文件 SGObject.cpp 第 41 行定义.
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在文件 SGObject.cpp 第 46 行定义.
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在文件 SGObject.cpp 第 51 行定义.
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在文件 SGObject.cpp 第 56 行定义.
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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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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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virtual |
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A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.
被 CGaussianKernel 重载.
在文件 SGObject.h 第 117 行定义.
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whether combination of inference method and given likelihood function supports binary classification
被 CLaplacianInferenceMethod , 以及 CEPInferenceMethod 重载.
在文件 InferenceMethod.h 第 346 行定义.
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whether combination of inference method and given likelihood function supports multiclass classification
在文件 InferenceMethod.h 第 353 行定义.
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重载 CInferenceMethod .
在文件 FITCInferenceMethod.h 第 190 行定义.
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unset generic type
this has to be called in classes specializing a template class
在文件 SGObject.cpp 第 235 行定义.
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protectedvirtual |
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protectedvirtual |
update matrices which are required to compute negative log marginal likelihood derivatives wrt hyperparameter
实现了 CInferenceMethod.
在文件 FITCInferenceMethod.cpp 第 266 行定义.
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Updates the hash of current parameter combination.
在文件 SGObject.cpp 第 187 行定义.
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io
在文件 SGObject.h 第 473 行定义.
alpha vector used in process mean calculation
在文件 InferenceMethod.h 第 441 行定义.
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features to use
在文件 InferenceMethod.h 第 435 行定义.
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parameters wrt which we can compute gradients
在文件 SGObject.h 第 488 行定义.
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Hash of parameter values
在文件 SGObject.h 第 494 行定义.
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covariance function
在文件 InferenceMethod.h 第 426 行定义.
kernel matrix from features (non-scalled by inference scalling)
在文件 InferenceMethod.h 第 450 行定义.
upper triangular factor of Cholesky decomposition
在文件 InferenceMethod.h 第 444 行定义.
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labels of features
在文件 InferenceMethod.h 第 438 行定义.
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mean function
在文件 InferenceMethod.h 第 429 行定义.
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likelihood function to use
在文件 InferenceMethod.h 第 432 行定义.
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model selection parameters
在文件 SGObject.h 第 485 行定义.
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map for different parameter versions
在文件 SGObject.h 第 491 行定义.
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parameters
在文件 SGObject.h 第 482 行定义.
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kernel scale
在文件 InferenceMethod.h 第 447 行定义.
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parallel
在文件 SGObject.h 第 476 行定义.
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version
在文件 SGObject.h 第 479 行定义.
