fig:scheme-d1
fig:plot-spc
fig:eberg-srs
fig:eberg-fs
fig:eberg-maxlike
fig:eberg-maxlike2
fig:eberg-fs2
fig:eberg-clhs
fig:eberg-lhs2
fig:eberg-fscs
fig:eberg-fscs-pnts
fig:eberg-allpnts
fig:eberg-grid-sample
fig:eberg-pred-erf
fig:eberg-iprob
fig:eberg-grid
fig:eberg-eml
fig:eberg-var-eml
fig:example-cv
fig:edgeroi-map
fig:edgeroi-grid-sample
fig:ac-soc1
fig:ac-soc2
fig:pred-soc
fig:edgeroi-var-eml
fig:ac-vw1
fig:ac-vw2
fig:eberg-pnts-eml
fig:scheme-resample
fig:summary-eberg
generating-spatial-sampling
spatial-sampling
response-surface-designs
spatial-sampling-algorithms-of-interest
ebergotzen-dataset
simple-random-sampling
latin-hypercube-sampling
feature-space-coverage-sampling
summary-points
resampling-methods-for-machine-learning
resampling-and-cross-validation
resampling-training-points-using-declustering
weighted-machine-learning
resampling-using-ensemble-ml
estimating-the-area-of-applicability
estimating-per-pixel-mapping-accuracy
testing-mapping-accuracy-using-resampling-and-blocking
resampling-for-spatiotemporal-machine-learning
case-study-cookfarm-dataset
generating-2nd-3rd-round-sampling
uncertainty-guided-sampling
summary-notes
which-sampling-algorithm-to-choose
sampling-in-a-new-area
ml-on-clustered-point-samples
references
