AddData(const af::array Ytrain) | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | privatevirtual |
afBias | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | private |
afIndexes | NeuralEngine::MachineLearning::IModel< Scalar > | private |
afSegments | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | private |
afX | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | private |
afY | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | private |
bInit | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | private |
boost::serialization::access (defined in NeuralEngine::MachineLearning::GPModels::PowerEP::SGPLVM< Scalar >) | NeuralEngine::MachineLearning::GPModels::PowerEP::SGPLVM< Scalar > | friend |
FixInducing(bool isfixed) | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | privatevirtual |
FixKernelParameters(bool isfixed) | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | privatevirtual |
FixLikelihoodParameters(bool isfixed) | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | privatevirtual |
Function(const af::array &x, af::array &outGradient) | NeuralEngine::MachineLearning::IModel< Scalar > | privatevirtual |
GetBatchSize() | NeuralEngine::MachineLearning::IModel< Scalar > | private |
GetDataDimensionality() | NeuralEngine::MachineLearning::IModel< Scalar > | private |
GetDataLenght() | NeuralEngine::MachineLearning::IModel< Scalar > | private |
GetGPLayer() | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | private |
GetModelType() | NeuralEngine::MachineLearning::IModel< Scalar > | private |
GetNumParameters() override | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | privatevirtual |
GetParameters() override | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | privatevirtual |
GetPseudoInputs() | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | private |
GetSegments() | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | private |
GetTrainingData() | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | private |
GetTrainingInputs() | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | private |
GPBaseModel(const af::array &Y, LogLikType lType=LogLikType::Gaussian, ModelType mtype=ModelType::GPR) | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | private |
GPBaseModel() | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | private |
gpLayer | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | private |
iBatchSize | NeuralEngine::MachineLearning::IModel< Scalar > | private |
iD | NeuralEngine::MachineLearning::IModel< Scalar > | private |
ik | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | private |
IModel(int numData, int numDimension, ModelType type) | NeuralEngine::MachineLearning::IModel< Scalar > | private |
iN | NeuralEngine::MachineLearning::IModel< Scalar > | private |
Init() override | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | privatevirtual |
iq | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | private |
likLayer | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | private |
m_dType | NeuralEngine::MachineLearning::IModel< Scalar > | private |
mType (defined in NeuralEngine::MachineLearning::IModel< Scalar >) | NeuralEngine::MachineLearning::IModel< Scalar > | private |
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) | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | privatevirtual |
PredictF(const af::array &testInputs, af::array &mf, af::array &vf) override | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | privatevirtual |
PredictY(const af::array &testInputs, af::array &my, af::array &vy) | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | privatevirtual |
SampleY(const af::array inputs, int numSamples, af::array &outFunctions) override | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | privatevirtual |
serialize(Archive &ar, unsigned int version) (defined in NeuralEngine::MachineLearning::GPModels::PowerEP::SGPLVM< Scalar >) | NeuralEngine::MachineLearning::GPModels::PowerEP::SGPLVM< Scalar > | inlineprivate |
SetBatchSize(int size) | NeuralEngine::MachineLearning::IModel< Scalar > | privatevirtual |
SetIndexes(af::array &indexes) | NeuralEngine::MachineLearning::IModel< Scalar > | private |
SetParameters(const af::array ¶m) override | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | privatevirtual |
SetSegments(af::array segments) | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | private |
SetTrainingData(af::array &data) | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | private |
SetTrainingInputs(af::array &inputs) | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | private |
SparseGPBaseModel(const af::array &Y, const af::array &X, int numInducing=200, LogLikType lType=LogLikType::Gaussian) | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | private |
SparseGPBaseModel() | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | private |
UpdateParameters() override | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | privatevirtual |
~GPBaseModel() | NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar > | privatevirtual |
~SparseGPBaseModel() | NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar > | privatevirtual |