bayesopt::KernelRegressor Member List

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

addNewPointToCholesky(const vectord &correlation, double selfcorrelation)	bayesopt::KernelRegressor	inlineprivate
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
create(size_t dim, Parameters parameters, const Dataset &data, MeanModel &mean, randEngine &eng)	bayesopt::NonParametricProcess	static
dim_ (defined in bayesopt::NonParametricProcess)	bayesopt::NonParametricProcess	protected
evaluate(const vectord &query)=0 (defined in bayesopt::RBOptimizable)	bayesopt::RBOptimizable	pure virtual
fitSurrogateModel()	bayesopt::KernelRegressor	inlinevirtual
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
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
mRegularizer	bayesopt::KernelRegressor	private
mScoreType (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor	protected
mSigma	bayesopt::NonParametricProcess	protected
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()=0	bayesopt::KernelRegressor	protectedpure virtual
prediction(const vectord &query)=0	bayesopt::NonParametricProcess	pure virtual
RBOptimizable() (defined in bayesopt::RBOptimizable)	bayesopt::RBOptimizable	inline
setHyperParameters(const vectord &theta) (defined in bayesopt::KernelRegressor)	bayesopt::KernelRegressor	inlinevirtual
updateSurrogateModel()	bayesopt::KernelRegressor	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