Kernel Deep Stacking Networks

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Documentation for package ‘kernDeepStackNet’ version 2.0.2

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kernDeepStackNet-package Kernel deep stacking networks with random Fourier transformation
calcTrA Calculates the trace of the hat matrix
calcTrAFast Calculates the trace of the hat matrix as C version
calcWdiag Calculation of weight matrix
cancorRed Calculate first canonical correlation
crossprodRcpp Calculates the cross product of a matrix
devStandard Predictive deviance of a linear model
EImod Expected improvement criterion replacement function
fineTuneCvKDSN Fine tuning of random weights of a given KDSN model
fitEnsembleKDSN Fit an ensemble of KDSN (experimental)
fitKDSN Fit kernel deep stacking network with random Fourier transformations
fourierTransPredict Prediction based on random Fourier transformation
gDerivMu Derivative of the link function evaluated at the expected values
getEigenValuesRcpp Calculates the eigenvalues of a matrix
kernDeepStackNet Kernel deep stacking networks with random Fourier transformation
kernDeepStackNet_crossprodRcpp Calculates the cross product of a matrix
kernDeepStackNet_getEigenValuesRcpp Calculates the eigenvalues of a matrix
lossApprox Kernel deep stacking network loss function
lossCvKDSN Kernel deep stacking network loss function based on cross-validation
lossGCV Generalized cross-validation loss
lossSharedCvKDSN Kernel deep stacking network loss function based on cross-validation and shared hyperparameters
lossSharedTestKDSN Kernel deep stacking network loss function with test set and shared hyperparameters
mbo1d Efficient global optimization with iterative point proposals
mboAll Efficient global optimization inclusive meta model validation
optimize1dMulti One dimensional optimization of multivariate loss functions
predict.KDSN Predict kernel deep stacking networks
predict.KDSNensemble Predict kernel deep stacking networks ensembles (experimental)
predict.KDSNensembleDisk Predict kernel deep stacking networks ensembles (experimental)
predLogProb Predictive logarithmic probability of Kriging model
randomFourierTrans Random Fourier transformation
rdcPart Randomized dependence coefficient partial calculation
rdcSubset Randomized dependence coefficients score on given subset
rdcVarOrder Variable ordering using randomized dependence coefficients (experimental)
rdcVarSelSubset Variable selection based on RDC with genetic algorithm (experimental)
robustStandard Robust standardization
tuneMboLevelCvKDSN Tuning of KDSN with efficient global optimization given level by cross-validation
tuneMboLevelGcvKDSN Tuning of KDSN with efficient global optimization given level by cross-validation
tuneMboSharedCvKDSN Tuning of KDSN with efficient global optimization given level by cross-validation and shared hyperparameters
tuneMboSharedSubsetKDSN Tuning subsets of KDSN with efficient global optimization and shared hyperparameters (experimental)
varMu Variance function evaluated at expected value