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| SparseDeepGPLVMBaseModel (const af::array &Y, int latentDimension, HiddenLayerDescription description, Scalar priorMean=0.0, Scalar priorVariance=1.0, LogLikType lType=LogLikType::Gaussian, XInit emethod=XInit::pca) |
| Constructor. More...
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| SparseDeepGPLVMBaseModel (const af::array &Y, int latentDimension, std::vector< HiddenLayerDescription > descriptions, Scalar priorMean=0.0, Scalar priorVariance=1.0, LogLikType lType=LogLikType::Gaussian, XInit emethod=XInit::pca) |
| Constructor. More...
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| SparseDeepGPLVMBaseModel () |
| Default Constructor. More...
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virtual | ~SparseDeepGPLVMBaseModel () |
| Destructor. More...
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virtual bool | Init () override |
| Initializes the model. More...
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virtual void | PredictF (const af::array &testInputs, af::array &mf, af::array &vf) override |
| Predict noise free functions values \(\mathbf{F}_*\). More...
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virtual void | SampleY (const af::array inputs, int numSamples, af::array &outFunctions) override |
| Generate function samples from posterior. More...
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virtual int | GetNumParameters () override |
| Gets number of parameters. More...
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virtual int | GetNumGPLayerParameters () |
| Gets number gp layer parameters. More...
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virtual void | SetParameters (const af::array ¶m) override |
| Sets the parameters for each optimization iteration. More...
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virtual af::array | GetParameters () override |
| Gets the parameters for each optimization iteration. More...
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virtual void | UpdateParameters () override |
| Updates the parameters. More...
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virtual int | GetNumLayers () |
| Gets number of GP layers. More...
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virtual std::vector< SparseGPBaseLayer< Scalar > * > | GetGPLayers () |
| Gets vector of GP layers. More...
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virtual void | FixKernelParameters (bool isfixed) |
| Sets fixation for hyperparameters. More...
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| GPLVMBaseModel (const af::array &Y, int latentDimension, Scalar priorMean=0.0, Scalar priorVariance=1.0, LogLikType lType=LogLikType::Gaussian, XInit emethod=XInit::pca) |
| Constructor. More...
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| GPLVMBaseModel () |
| Default constructor. More...
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virtual | ~GPLVMBaseModel () |
| Destructor. More...
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virtual void | Optimise (OptimizerType method=L_BFGS, Scalar tol=0.0, bool reinit_hypers=true, int maxiter=1000, int mb_size=0, LineSearchType lsType=MoreThuente, bool disp=true, int *cycle=nullptr) override |
| Optimizes the model parameters for best fit. More...
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virtual bool | Init (af::array &mx) |
| Initializes the model. More...
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virtual bool | Init () override |
| Initializes the model. More...
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virtual void | PosteriorLatents (af::array &mx, af::array &vx) |
| Get posterior distribution of latent variables /f$\mathbf{X}/f$. More...
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virtual int | GetNumParameters () override |
| Gets number of parameters. More...
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virtual void | SetParameters (const af::array ¶m) override |
| Sets the parameters for each optimization iteration. More...
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virtual af::array | GetParameters () override |
| Gets the parameters for each optimization iteration. More...
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virtual void | UpdateParameters () override |
| Updates the parameters. More...
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virtual void | FixKernelParameters (bool isfixed) |
| Sets fixation for hyperparameters. More...
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virtual void | FixInducing (bool isfixed) |
| Set fixation for inducing inputs. More...
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void | FixLatents (bool isFixed) |
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af::array | GetMeanGradient () |
| Gets prior mean gradient. More...
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af::array | GetVarGradient () |
| Gets prior variance gradient. More...
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void | SetPrior (const af::array mean, const af::array var) |
| Sets the prior. More...
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void | SetPriorCavity (const af::array meanCav, const af::array varCav) |
| Sets the cavity prior. More...
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void | SetLatentGradient (const af::array &dmParent, const af::array &dvParent) |
| Sets latent gradient. More...
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void | SetLatentGradientCavity (const af::array &dmParent, const af::array &dvParent) |
| Sets the latent cavity gradient. More...
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int | GetLatentDimension () |
| Gets latent dimension. More...
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void | SetBackConstraint (IBackconstraint< Scalar > *constraint) |
| Sets a back-constraint. More...
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IBackconstraint< Scalar > * | GetBackConstraint () |
| Gets the back-constraint. More...
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void | SetStyles (std::map< std::string, Style< Scalar > > *styles) |
| Sets the syles. More...
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void | AddStyle (Style< Scalar > style) |
| Adds a style. More...
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std::map< std::string, Style< Scalar > > * | GetStyles () |
| Gets the styles. More...
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| GPBaseModel (const af::array &Y, LogLikType lType=LogLikType::Gaussian, ModelType mtype=ModelType::GPR) |
| Constructor. More...
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| GPBaseModel () |
| Default Constructor. More...
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virtual | ~GPBaseModel () |
| Destructor. More...
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virtual void | Optimise (OptimizerType method=L_BFGS, Scalar tol=0.0, bool reinit_hypers=true, int maxiter=1000, int mb_size=0, LineSearchType lsType=MoreThuente, bool disp=true, int *cycle=nullptr) |
| Optimizes the model parameters for best fit. More...
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virtual bool | Init () |
| Initializes the model. More...
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virtual void | PredictF (const af::array &testInputs, af::array &mf, af::array &vf) |
| Predict noise free functions values \(\mathbf{F}_*\). More...
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virtual void | PredictY (const af::array &testInputs, af::array &my, af::array &vy) |
| Prediction of test outputs \(\mathbf{Y}_*\). More...
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virtual void | SampleY (const af::array inputs, int numSamples, af::array &outFunctions) |
| Generate function samples from posterior. More...
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virtual void | AddData (const af::array Ytrain) |
| Adds training data to the model. More...
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af::array | GetTrainingData () |
| Gets the training data set Y. More...
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void | SetTrainingData (af::array &data) |
| Sets training data Y. More...
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virtual int | GetNumParameters () |
| Gets number of parameters. More...
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virtual void | SetParameters (const af::array ¶m) |
| Sets the parameters for each optimization iteration. More...
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virtual af::array | GetParameters () |
| Gets the parameters for each optimization iteration. More...
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virtual void | UpdateParameters () |
| Updates the parameters. More...
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virtual void | FixLikelihoodParameters (bool isfixed) |
| Sets the likelihood parameters to be fixed or not for optimization. More...
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void | SetSegments (af::array segments) |
| Sets fixation for hyperparameters. More...
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af::array | GetSegments () |
| Gets the start index array for the sequences. More...
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virtual Scalar | Function (const af::array &x, af::array &outGradient) |
| Cost function the given x inputs. More...
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virtual int | GetNumParameters ()=0 |
| Gets number of parameters to be optimized. More...
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virtual void | SetParameters (const af::array ¶m)=0 |
| Sets the parameters for each optimization iteration. More...
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virtual af::array | GetParameters ()=0 |
| Gets the parameters for each optimization iteration. More...
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virtual void | UpdateParameters ()=0 |
| Updates the parameters. More...
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int | GetDataLenght () |
| Gets data lenght. More...
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int | GetDataDimensionality () |
| Gets data dimensionality. More...
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ModelType | GetModelType () |
| Gets model type. More...
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virtual void | SetBatchSize (int size) |
| Sets batch size. More...
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int | GetBatchSize () |
| Gets batch size. More...
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void | SetIndexes (af::array &indexes) |
| Sets the batch indexes. More...
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| GPNode () |
| Default constructor. More...
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virtual | ~GPNode () |
| Destructor. More...
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int | GetNumChildren () const |
| Gets the number of children of this item. More...
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int | AttachChild (std::shared_ptr< GPNode< Scalar > > const &child) |
| Attaches a child. More...
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int | DetachChild (std::shared_ptr< GPNode< Scalar > > const &child) |
| Detaches a child. More...
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std::shared_ptr< GPNode< Scalar > > | DetachChildAt (int i) |
| Detaches a child at index. More...
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void | DetachAllChildren () |
| Detach all children from this node. More...
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std::shared_ptr< GPNode< Scalar > > | SetChild (int i, std::shared_ptr< GPNode< Scalar > > const &child) |
| Sets a child. More...
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std::shared_ptr< GPNode< Scalar > > | GetChild (int i) |
| Gets a child at index. More...
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GPNode< Scalar > * | GetParent () |
| Access to the parent object, which is null for the root of the hierarchy. More...
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void | SetParent (GPNode< Scalar > *parent) |
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Access to the parent object. Node calls this during attach/detach of children. More...
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template<typename
Scalar>
class NeuralEngine::MachineLearning::GPModels::SparseDeepGPLVMBaseModel< Scalar >
Base class with abstract and basic function definitions. All deep GP models will be derived from this class.
HmetalT, 26.10.2017.
Definition at line 49 of file FgSparseDeepGPLVMBaseModel.h.