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SHOGUN
4.1.0
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The sparse inference base class for classification and regression for 1-D labels (1D regression and binary classification)
在文件 SingleSparseInferenceBase.h 第 48 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 |
静态 Protected 成员函数 | |
| static void * | get_derivative_helper (void *p) |
default constructor
在文件 SingleSparseInferenceBase.cpp 第 48 行定义.
| CSingleSparseInferenceBase | ( | CKernel * | kernel, |
| CFeatures * | features, | ||
| CMeanFunction * | mean, | ||
| CLabels * | labels, | ||
| CLikelihoodModel * | model, | ||
| CFeatures * | inducing_features | ||
| ) |
constructor
| kernel | covariance function |
| features | features to use in inference |
| mean | mean function |
| labels | labels of the features |
| model | likelihood model to use |
| inducing_features | features to use |
在文件 SingleSparseInferenceBase.cpp 第 53 行定义.
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virtual |
在文件 SingleSparseInferenceBase.cpp 第 91 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.
check the bound constraint is vailid or not
| bound | bound constrains of inducing features |
| name | the name of the bound |
在文件 SingleSparseInferenceBase.cpp 第 202 行定义.
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protectedvirtualinherited |
check whether features and inducing features are set
在文件 SparseInferenceBase.cpp 第 49 行定义.
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protectedvirtual |
check whether the provided kernel can compute the gradient wrt inducing features
Note that currently we check the name of the provided kernel to determine whether the kernel can compute the derivatives wrt inducing_features
The name of a supported Kernel must end with "SparseKernel"
在文件 SingleSparseInferenceBase.cpp 第 96 行定义.
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protectedvirtualinherited |
check if members of object are valid for inference
重载 CInferenceMethod .
被 CFITCInferenceMethod , 以及 CSparseVGInferenceMethod 重载.
在文件 SparseInferenceBase.cpp 第 128 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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protectedvirtualinherited |
update gradients
被 CKLInferenceMethod, CExactInferenceMethod, CEPInferenceMethod, CSparseVGInferenceMethod, CSingleFITCLaplacianInferenceMethod, CFITCInferenceMethod , 以及 CLaplacianInferenceBase 重载.
在文件 InferenceMethod.cpp 第 330 行定义.
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protectedvirtualinherited |
convert inducing features and features to the same represention
Note that these two kinds of features can be different types. The reasons are listed below.
在文件 SparseInferenceBase.cpp 第 54 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.
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virtual |
whether enable to opitmize inducing features
| is_optmization | enable optimization |
在文件 SingleSparseInferenceBase.cpp 第 257 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.
get alpha vector
\[ \mu = K\alpha \]
where \(\mu\) is the mean and \(K\) is the prior covariance matrix.
在文件 SparseInferenceBase.cpp 第 136 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.
在文件 SparseInferenceBase.cpp 第 145 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 255 行定义.
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protectedpure virtual |
compute variables which are required to compute negative log marginal likelihood full derivatives wrt cov-like hyperparameter \(\theta\)
Note that scale, which is a hyperparameter in inference_method, is a cov-like hyperparameter hyperparameters in cov function are cov-like hyperparameters
| ddiagKi | \(\textbf{diag}(\frac{\partial {\Sigma_{n}}}{\partial {\theta}})\) |
| dKuui | \(\frac{\partial {\Sigma_{m}}}{\partial {\theta}}\) |
| dKui | \(\frac{\partial {\Sigma_{m,n}}}{\partial {\theta}}\) |
在 CSingleFITCLaplacianInferenceMethod, CSparseVGInferenceMethod , 以及 CSingleFITCLaplacianBase 内被实现.
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protectedpure virtual |
returns derivative of negative log marginal likelihood wrt inducing features (input) Note that in order to call this method, kernel must support Sparse inference, which means derivatives wrt inducing features can be computed
Note that the kernel must support to compute the derivatives wrt inducing features
| param | parameter of given kernel |
实现了 CSparseInferenceBase.
在 CSingleFITCLaplacianInferenceMethod, CSingleFITCLaplacianBase , 以及 CSparseVGInferenceMethod 内被实现.
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protectedpure virtual |
returns derivative of negative log marginal likelihood wrt inducing noise
| param | parameter of given inference class |
实现了 CSparseInferenceBase.
在 CSingleFITCLaplacianInferenceMethod, CSparseVGInferenceMethod , 以及 CSingleFITCLaplacianBase 内被实现.
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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 CSparseInferenceBase.
被 CSingleFITCLaplacianInferenceMethod 重载.
在文件 SingleSparseInferenceBase.cpp 第 108 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 CSparseInferenceBase.
被 CSingleFITCLaplacianInferenceMethod 重载.
在文件 SingleSparseInferenceBase.cpp 第 160 行定义.
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protectedpure virtualinherited |
returns derivative of negative log marginal likelihood wrt parameter of likelihood model
| param | parameter of given likelihood model |
实现了 CInferenceMethod.
在 CSingleFITCLaplacianInferenceMethod, CSingleFITCLaplacianBase, CFITCInferenceMethod , 以及 CSparseVGInferenceMethod 内被实现.
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protectedpure virtualinherited |
returns derivative of negative log marginal likelihood wrt mean function's parameter
| param | parameter of given mean function |
实现了 CInferenceMethod.
在 CSingleFITCLaplacianInferenceMethod, CSparseVGInferenceMethod , 以及 CSingleFITCLaplacianBase 内被实现.
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virtualinherited |
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inherited |
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inherited |
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inherited |
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virtualinherited |
get the gradient
| parameters | parameter's dictionary |
在文件 InferenceMethod.h 第 245 行定义.
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virtualinherited |
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virtualinherited |
get the noise for inducing points
在文件 SparseInferenceBase.cpp 第 119 行定义.
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virtualinherited |
return what type of inference we are
重载 CInferenceMethod .
被 CSingleFITCLaplacianInferenceMethod, CFITCInferenceMethod , 以及 CSparseVGInferenceMethod 重载.
在文件 SparseInferenceBase.h 第 97 行定义.
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virtualinherited |
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virtualinherited |
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inherited |
Computes an unbiased estimate of the marginal-likelihood (in log-domain),
\[ p(y|X,\theta), \]
where \(y\) are the labels, \(X\) are the features (omitted from in the following expressions), and \(\theta\) represent hyperparameters.
This is done via a Gaussian 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). Storing all number of log-domain ensures numerical stability.
| 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 covariance matrix is not numerically positive semi-definite. |
在文件 InferenceMethod.cpp 第 126 行定义.
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virtualinherited |
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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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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.
get the E matrix used for multi classification
在文件 InferenceMethod.cpp 第 72 行定义.
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virtual |
returns the name of the inference method
重载 CSparseInferenceBase .
被 CSingleFITCLaplacianBase, CSingleFITCLaplacianInferenceMethod, CSingleFITCLaplacianInferenceMethodWithLBFGS, CFITCInferenceMethod , 以及 CSparseVGInferenceMethod 重载.
在文件 SingleSparseInferenceBase.h 第 73 行定义.
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pure virtualinherited |
get negative log marginal likelihood
\[ -log(p(y|X, \theta)) \]
where \(y\) are the labels, \(X\) are the features, and \(\theta\) represent hyperparameters.
在 CSingleFITCLaplacianInferenceMethod, CMultiLaplacianInferenceMethod, CKLInferenceMethod, CExactInferenceMethod, CFITCInferenceMethod, CSparseVGInferenceMethod, CEPInferenceMethod , 以及 CSingleLaplacianInferenceMethod 内被实现.
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virtualinherited |
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 185 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 CFITCInferenceMethod, CSparseVGInferenceMethod , 以及 CSingleFITCLaplacianInferenceMethod 内被实现.
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 CFITCInferenceMethod, CSparseVGInferenceMethod , 以及 CSingleFITCLaplacianInferenceMethod 内被实现.
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virtualinherited |
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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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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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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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virtual |
opitmize inducing features
在文件 SingleSparseInferenceBase.cpp 第 262 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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virtualinherited |
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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 |
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set the noise for inducing points
| noise | noise for inducing points |
The noise is used to enfore the kernel matrix about the inducing points are positive definite
在文件 SparseInferenceBase.cpp 第 113 行定义.
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virtual |
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virtualinherited |
set the lower bound of inducing features
| bound | lower bound constrains of inducing features |
Note that if the length of the bound is 1, it means the bound constraint applies to each dimension of all inducing features
Note that if the length of the bound is greater than 1, it means each dimension of the bound constraint applies to the corresponding dimension of inducing features
在文件 SingleSparseInferenceBase.cpp 第 219 行定义.
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virtual |
set the max number of iterations used in optimization of inducing features
| it | max number of iterations |
在文件 SingleSparseInferenceBase.cpp 第 230 行定义.
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virtualinherited |
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set likelihood model
| mod | model to set |
被 CKLInferenceMethod , 以及 CKLDualInferenceMethod 重载.
在文件 InferenceMethod.h 第 340 行定义.
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virtual |
set the tolearance used in optimization of inducing features
| tol | tolearance |
在文件 SingleSparseInferenceBase.cpp 第 235 行定义.
set the upper bound of inducing features
| bound | upper bound constrains of inducing features |
Note that if the length of the bound is 1, it means the bound constraint applies to each dimension of all inducing features
Note that if the length of the bound is greater than 1, it means each dimension of the bound constraint applies to the corresponding dimension of inducing features
在文件 SingleSparseInferenceBase.cpp 第 224 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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virtualinherited |
whether combination of inference method and given likelihood function supports binary classification
被 CEPInferenceMethod, CKLInferenceMethod, CSingleFITCLaplacianInferenceMethod , 以及 CSingleLaplacianInferenceMethod 重载.
在文件 InferenceMethod.h 第 371 行定义.
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virtualinherited |
whether combination of inference method and given likelihood function supports multiclass classification
在文件 InferenceMethod.h 第 378 行定义.
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virtualinherited |
whether combination of inference method and given likelihood function supports regression
被 CExactInferenceMethod, CKLInferenceMethod, CFITCInferenceMethod, CSparseVGInferenceMethod, CSingleFITCLaplacianInferenceMethod , 以及 CSingleLaplacianInferenceMethod 重载.
在文件 InferenceMethod.h 第 364 行定义.
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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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pure virtualinherited |
update all matrices
重载 CInferenceMethod .
在 CSingleFITCLaplacianInferenceMethod, CFITCInferenceMethod , 以及 CSparseVGInferenceMethod 内被实现.
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protectedpure virtualinherited |
update alpha vector
在 CEPInferenceMethod, CSingleFITCLaplacianInferenceMethod, CExactInferenceMethod, CSingleFITCLaplacianBase, CFITCInferenceMethod, CSparseVGInferenceMethod, CMultiLaplacianInferenceMethod, CKLDualInferenceMethod, CSingleLaplacianInferenceMethodWithLBFGS, CSingleFITCLaplacianInferenceMethodWithLBFGS, CSingleLaplacianInferenceMethod, CKLCovarianceInferenceMethod, CKLApproxDiagonalInferenceMethod , 以及 CKLCholeskyInferenceMethod 内被实现.
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protectedpure virtualinherited |
update cholesky matrix
在 CEPInferenceMethod, CSingleFITCLaplacianInferenceMethod, CExactInferenceMethod, CSingleFITCLaplacianBase, CFITCInferenceMethod, CSparseVGInferenceMethod, CMultiLaplacianInferenceMethod, CKLDualInferenceMethod, CSingleLaplacianInferenceMethod, CKLCovarianceInferenceMethod , 以及 CKLLowerTriangularInferenceMethod 内被实现.
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protectedpure virtualinherited |
update matrices which are required to compute negative log marginal likelihood derivatives wrt hyperparameter
在 CEPInferenceMethod, CSingleFITCLaplacianInferenceMethod, CExactInferenceMethod, CSingleFITCLaplacianBase, CFITCInferenceMethod, CSparseVGInferenceMethod, CMultiLaplacianInferenceMethod, CKLDualInferenceMethod, CSingleLaplacianInferenceMethod, CKLCovarianceInferenceMethod , 以及 CKLLowerTriangularInferenceMethod 内被实现.
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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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protectedvirtualinherited |
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io
在文件 SGObject.h 第 369 行定义.
alpha vector used in process mean calculation
在文件 InferenceMethod.h 第 475 行定义.
the matrix used for multi classification
在文件 InferenceMethod.h 第 487 行定义.
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protectedinherited |
features to use
在文件 InferenceMethod.h 第 469 行定义.
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protected |
在文件 SingleSparseInferenceBase.h 第 219 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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protectedinherited |
Whether gradients are updated
在文件 InferenceMethod.h 第 490 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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protected |
tolearance used in optimizing inducing_features
在文件 SingleSparseInferenceBase.h 第 193 行定义.
inducing features for approximation
在文件 SparseInferenceBase.h 第 305 行定义.
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protectedinherited |
covariance function
在文件 InferenceMethod.h 第 460 行定义.
kernel matrix from features (non-scalled by inference scalling)
在文件 InferenceMethod.h 第 484 行定义.
diagonal elements of kernel matrix m_ktrtr
在文件 SparseInferenceBase.h 第 323 行定义.
covariance matrix of inducing features and training features
在文件 SparseInferenceBase.h 第 314 行定义.
covariance matrix of inducing features
在文件 SparseInferenceBase.h 第 311 行定义.
upper triangular factor of Cholesky decomposition
在文件 InferenceMethod.h 第 478 行定义.
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protectedinherited |
labels of features
在文件 InferenceMethod.h 第 472 行定义.
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protected |
在文件 SingleSparseInferenceBase.h 第 222 行定义.
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protectedinherited |
noise of the inducing variables
在文件 SparseInferenceBase.h 第 308 行定义.
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protectedinherited |
kernel scale
在文件 InferenceMethod.h 第 481 行定义.
lower bound of inducing features
在文件 SingleSparseInferenceBase.h 第 184 行定义.
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protected |
max number of iterations
在文件 SingleSparseInferenceBase.h 第 190 行定义.
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protectedinherited |
mean function
在文件 InferenceMethod.h 第 463 行定义.
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protectedinherited |
likelihood function to use
在文件 InferenceMethod.h 第 466 行定义.
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inherited |
model selection parameters
在文件 SGObject.h 第 381 行定义.
mean vector of the the posterior Gaussian distribution
在文件 SparseInferenceBase.h 第 320 行定义.
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protected |
whether optimize inducing features
在文件 SingleSparseInferenceBase.h 第 196 行定义.
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inherited |
parameters
在文件 SGObject.h 第 378 行定义.
covariance matrix of the the posterior Gaussian distribution
在文件 SparseInferenceBase.h 第 317 行定义.
upper bound of inducing features
在文件 SingleSparseInferenceBase.h 第 187 行定义.
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parallel
在文件 SGObject.h 第 372 行定义.
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version
在文件 SGObject.h 第 375 行定义.
