bayesopt::GaussianProcess Member List

This is the complete list of members for bayesopt::GaussianProcess, including all inherited members.

computeCholeskyCorrelation()	bayesopt::KernelRegressor	protected
computeCorrMatrix(matrixd &corrMatrix)	bayesopt::KernelRegressor	inlineprotected
computeCorrMatrix()	bayesopt::KernelRegressor	inlineprotected
computeCrossCorrelation(const vectord &query) (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor	inlineprotected
computeDerivativeCorrMatrix(int dth_index)	bayesopt::KernelRegressor	protected
computeSelfCorrelation(const vectord &query) (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor	inlineprotected
ConditionalBayesProcess(size_t dim, Parameters parameters, const Dataset &data, MeanModel &mean, randEngine &eng) (defined in bayesopt::ConditionalBayesProcess)	bayesopt::ConditionalBayesProcess
create(size_t dim, Parameters parameters, const Dataset &data, MeanModel &mean, randEngine &eng)	bayesopt::NonParametricProcess	static
d_	bayesopt::GaussianProcess	private
dim_ (defined in bayesopt::NonParametricProcess)	bayesopt::NonParametricProcess	protected
evaluate(const vectord &x)	bayesopt::ConditionalBayesProcess	inlinevirtual
evaluateKernelParams()	bayesopt::ConditionalBayesProcess
fitSurrogateModel()	bayesopt::KernelRegressor	inlinevirtual
GaussianProcess(size_t dim, Parameters params, const Dataset &data, MeanModel &mean, randEngine &eng) (defined in bayesopt::GaussianProcess)	bayesopt::GaussianProcess
getData() (defined in bayesopt::NonParametricProcess)	bayesopt::NonParametricProcess	inline
getHyperParameters() (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor	inlinevirtual
getSignalVariance() (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor
getValueAtMinimum() (defined in bayesopt::NonParametricProcess)	bayesopt::NonParametricProcess	inline
KernelRegressor(size_t dim, Parameters parameters, const Dataset &data, MeanModel &mean, randEngine &eng) (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor
mAlphaV	bayesopt::GaussianProcess	private
mData (defined in bayesopt::NonParametricProcess)	bayesopt::NonParametricProcess	protected
mKernel (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor	protected
mL	bayesopt::KernelRegressor	protected
mLearnAll (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor	protected
mLearnType (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor	protected
mMean (defined in bayesopt::NonParametricProcess)	bayesopt::NonParametricProcess	protected
mScoreType (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor	protected
mSigma	bayesopt::NonParametricProcess	protected
negativeLogLikelihood()	bayesopt::GaussianProcess	privatevirtual
negativeTotalLogLikelihood()	bayesopt::GaussianProcess	privatevirtual
nHyperParameters() (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor	inlinevirtual
NonParametricProcess(size_t dim, Parameters parameters, const Dataset &data, MeanModel &mean, randEngine &eng) (defined in bayesopt::NonParametricProcess)	bayesopt::NonParametricProcess
precomputePrediction()	bayesopt::GaussianProcess	privatevirtual
prediction(const vectord &query)	bayesopt::GaussianProcess	virtual
RBOptimizable() (defined in bayesopt::RBOptimizable)	bayesopt::RBOptimizable	inline
setHyperParameters(const vectord &theta) (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor	inlinevirtual
updateSurrogateModel()	bayesopt::KernelRegressor	virtual
~ConditionalBayesProcess() (defined in bayesopt::ConditionalBayesProcess)	bayesopt::ConditionalBayesProcess	virtual
~GaussianProcess() (defined in bayesopt::GaussianProcess)	bayesopt::GaussianProcess	virtual
~KernelRegressor() (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor	virtual
~NonParametricProcess() (defined in bayesopt::NonParametricProcess)	bayesopt::NonParametricProcess	virtual
~RBOptimizable() (defined in bayesopt::RBOptimizable)	bayesopt::RBOptimizable	inlinevirtual