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| | SparseDeepGPBaseModel (const af::array &Y, const af::array &X, HiddenLayerDescription hiddenLayerdescription, LogLikType lType=LogLikType::Gaussian) |
| | Constructor. More...
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| | SparseDeepGPBaseModel (const af::array &Y, const af::array &X, std::vector< HiddenLayerDescription > hiddenLayerdescriptions, LogLikType lType=LogLikType::Gaussian) |
| | Constructor. More...
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| | SparseDeepGPBaseModel () |
| | Default Constructor. More...
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| virtual | ~SparseDeepGPBaseModel () |
| | Destructor. More...
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| virtual bool | Init () override |
| | Initializes the model. More...
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| af::array | GetTrainingInputs () |
| | Gets training inputs. More...
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| virtual void | FixInducing (bool isfixed) |
| | Set fixation for inducing inputs. More...
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| | DeepGPBaseModel (const af::array &Y, HiddenLayerDescription hiddenLayerdescription, LogLikType lType=LogLikType::Gaussian) |
| | Constructor. More...
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| | DeepGPBaseModel (const af::array &Y, std::vector< HiddenLayerDescription > descriptions, LogLikType lType=LogLikType::Gaussian) |
| | Constructor. More...
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| | DeepGPBaseModel () |
| | Default Constructor. More...
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| virtual | ~DeepGPBaseModel () |
| | Destructor. 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 | GetNumLayers () |
| | Gets number of GP layers. 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 std::vector< GPBaseLayer< 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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| | 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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template<typename
Scalar>
class NeuralEngine::MachineLearning::GPModels::SparseDeepGPBaseModel< 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 31 of file FgSparseDeepGPBaseModel.h.