Methods catalogue

Every native method in the library, grouped by the n4m.<role> namespace (ABI 2.0). Each row links to the method’s documentation page and shows its fully-qualified name n4m.<role>.<sub>...<leaf>. Parameters, bibliographic sources, mathematical principles, binding signatures, and benchmark rows are on the linked pages.

Total catalogued native methods: 209. Additional Python reference surfaces are documented where relevant.

transform — fit/transform feature transforms

Method	Fully-qualified name	Namespace	Refs
cow_align	n4m.transform.alignment.cow_align	n4m.transform.alignment	C
dtw_align	n4m.transform.alignment.dtw_align	n4m.transform.alignment	C
icoshift_align	n4m.transform.alignment.icoshift_align	n4m.transform.alignment	C
xcorr_align	n4m.transform.alignment.xcorr_align	n4m.transform.alignment	C
airpls	n4m.transform.baseline.airpls	n4m.transform.baseline	C
arpls	n4m.transform.baseline.arpls	n4m.transform.baseline	C
asls	n4m.transform.baseline.asls	n4m.transform.baseline	C
beads	n4m.transform.baseline.beads	n4m.transform.baseline	C
detrend	n4m.transform.baseline.detrend	n4m.transform.baseline	C
iasls	n4m.transform.baseline.iasls	n4m.transform.baseline	C
imodpoly	n4m.transform.baseline.imodpoly	n4m.transform.baseline	C
modpoly	n4m.transform.baseline.modpoly	n4m.transform.baseline	C
rolling_ball	n4m.transform.baseline.rolling_ball	n4m.transform.baseline	C
saps	n4m.transform.baseline.saps	n4m.transform.baseline	C
snip	n4m.transform.baseline.snip	n4m.transform.baseline	C
osc	n4m.transform.orthogonalization.osc	n4m.transform.orthogonalization	C
crop	n4m.transform.resampling.crop	n4m.transform.resampling	C
kbins_discretizer	n4m.transform.resampling.kbins_discretizer	n4m.transform.resampling	C
range_discretizer	n4m.transform.resampling.range_discretizer	n4m.transform.resampling	C
resample_transformer	n4m.transform.resampling.resample_transformer	n4m.transform.resampling	C
resampler	n4m.transform.resampling.resampler	n4m.transform.resampling	C
baseline_center	n4m.transform.scaling.baseline_center	n4m.transform.scaling	C
log_transform	n4m.transform.scaling.log_transform	n4m.transform.scaling	C
normalize	n4m.transform.scaling.normalize	n4m.transform.scaling	C
simple_scale	n4m.transform.scaling.simple_scale	n4m.transform.scaling	C
area_normalization	n4m.transform.scatter.area_normalization	n4m.transform.scatter	C
emsc	n4m.transform.scatter.emsc	n4m.transform.scatter	C
local_centering	n4m.transform.scatter.local_centering	n4m.transform.scatter	C
local_snv	n4m.transform.scatter.local_snv	n4m.transform.scatter	C
localized_msc	n4m.transform.scatter.localized_msc	n4m.transform.scatter	C
msc	n4m.transform.scatter.msc	n4m.transform.scatter	C
piecewise_msc	n4m.transform.scatter.piecewise_msc	n4m.transform.scatter	C
piecewise_snv	n4m.transform.scatter.piecewise_snv	n4m.transform.scatter	C
robust_snv	n4m.transform.scatter.robust_snv	n4m.transform.scatter	C
snv	n4m.transform.scatter.snv	n4m.transform.scatter	C
vsn	n4m.transform.scatter.vsn	n4m.transform.scatter	C
weighted_snv	n4m.transform.scatter.weighted_snv	n4m.transform.scatter	C
fraction_to_percent	n4m.transform.signal_conversion.fraction_to_percent	n4m.transform.signal_conversion	C
from_absorbance	n4m.transform.signal_conversion.from_absorbance	n4m.transform.signal_conversion	C
kubelka_munk	n4m.transform.signal_conversion.kubelka_munk	n4m.transform.signal_conversion	C
percent_to_fraction	n4m.transform.signal_conversion.percent_to_fraction	n4m.transform.signal_conversion	C
signal_type_detector	n4m.transform.signal_conversion.signal_type_detector	n4m.transform.signal_conversion	C
to_absorbance	n4m.transform.signal_conversion.to_absorbance	n4m.transform.signal_conversion	C
derivative	n4m.transform.smoothing.derivative	n4m.transform.smoothing	C
first_derivative	n4m.transform.smoothing.first_derivative	n4m.transform.smoothing	C
gaussian	n4m.transform.smoothing.gaussian	n4m.transform.smoothing	C
norris_williams	n4m.transform.smoothing.norris_williams	n4m.transform.smoothing	C
savitzky_golay	n4m.transform.smoothing.savitzky_golay	n4m.transform.smoothing	C
second_derivative	n4m.transform.smoothing.second_derivative	n4m.transform.smoothing	C
fck_static	n4m.transform.specialized.fck_static	n4m.transform.specialized	C
haar	n4m.transform.wavelet.haar	n4m.transform.wavelet	C
wavelet	n4m.transform.wavelet.wavelet	n4m.transform.wavelet	C
wavelet_denoise	n4m.transform.wavelet.wavelet_denoise	n4m.transform.wavelet	C
wavelet_features	n4m.transform.wavelet.wavelet_features	n4m.transform.wavelet	C
wavelet_pca	n4m.transform.wavelet.wavelet_pca	n4m.transform.wavelet	C
wavelet_svd	n4m.transform.wavelet.wavelet_svd	n4m.transform.wavelet	C

augmentation — apply-only training-time perturbations

Method	Fully-qualified name	Namespace	Refs
linear_drift	n4m.augmentation.drift.linear_drift	n4m.augmentation.drift	C
path_length	n4m.augmentation.drift.path_length	n4m.augmentation.drift	C
poly_drift	n4m.augmentation.drift.poly_drift	n4m.augmentation.drift	C
detector_rolloff	n4m.augmentation.instrument.detector_rolloff	n4m.augmentation.instrument	C
edge_artifacts	n4m.augmentation.instrument.edge_artifacts	n4m.augmentation.instrument	C
edge_curvature	n4m.augmentation.instrument.edge_curvature	n4m.augmentation.instrument	C
moisture	n4m.augmentation.instrument.moisture	n4m.augmentation.instrument	C
stray_light	n4m.augmentation.instrument.stray_light	n4m.augmentation.instrument	C
temperature	n4m.augmentation.instrument.temperature	n4m.augmentation.instrument	C
truncated_peak	n4m.augmentation.instrument.truncated_peak	n4m.augmentation.instrument	C
local_mixup	n4m.augmentation.mixup.local_mixup	n4m.augmentation.mixup	C
mixup	n4m.augmentation.mixup.mixup	n4m.augmentation.mixup	C
random_x_op	n4m.augmentation.mixup.random_x_op	n4m.augmentation.mixup	C
rotate_translate	n4m.augmentation.mixup.rotate_translate	n4m.augmentation.mixup	C
gaussian_noise	n4m.augmentation.noise.gaussian_noise	n4m.augmentation.noise	C
hetero_noise	n4m.augmentation.noise.hetero_noise	n4m.augmentation.noise	C
multiplicative_noise	n4m.augmentation.noise.multiplicative_noise	n4m.augmentation.noise	C
spike_noise	n4m.augmentation.noise.spike_noise	n4m.augmentation.noise	C
batch_effect	n4m.augmentation.scattering.batch_effect	n4m.augmentation.scattering	C
dead_band	n4m.augmentation.scattering.dead_band	n4m.augmentation.scattering	C
emsc_distort	n4m.augmentation.scattering.emsc_distort	n4m.augmentation.scattering	C
instrument_broaden	n4m.augmentation.scattering.instrument_broaden	n4m.augmentation.scattering	C
particle_size	n4m.augmentation.scattering.particle_size	n4m.augmentation.scattering	C
scatter_sim_msc	n4m.augmentation.scattering.scatter_sim_msc	n4m.augmentation.scattering	C
band_mask	n4m.augmentation.spectral.band_mask	n4m.augmentation.spectral	C
band_perturb	n4m.augmentation.spectral.band_perturb	n4m.augmentation.spectral	C
channel_dropout	n4m.augmentation.spectral.channel_dropout	n4m.augmentation.spectral	C
gauss_jitter	n4m.augmentation.spectral.gauss_jitter	n4m.augmentation.spectral	C
local_clip	n4m.augmentation.spectral.local_clip	n4m.augmentation.spectral	C
magnitude_warp	n4m.augmentation.spectral.magnitude_warp	n4m.augmentation.spectral	C
unsharp_mask	n4m.augmentation.spectral.unsharp_mask	n4m.augmentation.spectral	C
spline_curve_simplification	n4m.augmentation.splines.spline_curve_simplification	n4m.augmentation.splines	C
spline_smoothing	n4m.augmentation.splines.spline_smoothing	n4m.augmentation.splines	C
spline_x_perturbations	n4m.augmentation.splines.spline_x_perturbations	n4m.augmentation.splines	C
spline_x_simplification	n4m.augmentation.splines.spline_x_simplification	n4m.augmentation.splines	C
spline_y_perturbations	n4m.augmentation.splines.spline_y_perturbations	n4m.augmentation.splines	C
local_warp	n4m.augmentation.wavelength.local_warp	n4m.augmentation.wavelength	C
wavelength_shift	n4m.augmentation.wavelength.wavelength_shift	n4m.augmentation.wavelength	C
wavelength_stretch	n4m.augmentation.wavelength.wavelength_stretch	n4m.augmentation.wavelength	C

estimators — supervised predictors (fit/predict)

Method	Fully-qualified name	Namespace	Refs
pls_lda	n4m.estimators.classification.pls_lda	n4m.estimators.classification	C
pls_logistic	n4m.estimators.classification.pls_logistic	n4m.estimators.classification	C
pls_qda	n4m.estimators.classification.pls_qda	n4m.estimators.classification	C
sparse_pls_da	n4m.estimators.classification.sparse_pls_da	n4m.estimators.classification	C
mb_pls	n4m.estimators.multiblock.mb_pls	n4m.estimators.multiblock	C
mir_pls	n4m.estimators.multiblock.mir_pls	n4m.estimators.multiblock	C
o2pls	n4m.estimators.multiblock.o2pls	n4m.estimators.multiblock	C
on_pls	n4m.estimators.multiblock.on_pls	n4m.estimators.multiblock	C
rosa	n4m.estimators.multiblock.rosa	n4m.estimators.multiblock	C
so_pls	n4m.estimators.multiblock.so_pls	n4m.estimators.multiblock	C
pls_glm	n4m.estimators.regression.glm.pls_glm	n4m.estimators.regression.glm	C
gpr_pls	n4m.estimators.regression.kernel.gpr_pls	n4m.estimators.regression.kernel	C
kernel_pls	n4m.estimators.regression.kernel.kernel_pls	n4m.estimators.regression.kernel	C
continuum_regression	n4m.estimators.regression.latent.continuum_regression	n4m.estimators.regression.latent	C, Py
cppls	n4m.estimators.regression.latent.cppls	n4m.estimators.regression.latent	C, Py
ecr	n4m.estimators.regression.latent.ecr	n4m.estimators.regression.latent	C, Py
missing_aware_nipals	n4m.estimators.regression.latent.missing_aware_nipals	n4m.estimators.regression.latent	C
pcr	n4m.estimators.regression.latent.pcr	n4m.estimators.regression.latent	C, Py
pls	n4m.estimators.regression.latent.pls	n4m.estimators.regression.latent	C, Py
lw_pls	n4m.estimators.regression.local.lw_pls	n4m.estimators.regression.local	C
recursive_pls	n4m.estimators.regression.online.recursive_pls	n4m.estimators.regression.online	C
ridge	n4m.estimators.regression.regularized.ridge	n4m.estimators.regression.regularized	C, Py
ridge_pls	n4m.estimators.regression.regularized.ridge_pls	n4m.estimators.regression.regularized	C, Py
robust_pls	n4m.estimators.regression.robust.robust_pls	n4m.estimators.regression.robust	C, Py
weighted_pls	n4m.estimators.regression.robust.weighted_pls	n4m.estimators.regression.robust	C, Py
fused_sparse_pls	n4m.estimators.regression.sparse.fused_sparse_pls	n4m.estimators.regression.sparse	C
group_sparse_pls	n4m.estimators.regression.sparse.group_sparse_pls	n4m.estimators.regression.sparse	C
sparse_simpls	n4m.estimators.regression.sparse.sparse_simpls	n4m.estimators.regression.sparse	C
n_pls	n4m.estimators.regression.tensor.n_pls	n4m.estimators.regression.tensor	C
pls_cox	n4m.estimators.survival.pls_cox	n4m.estimators.survival	C

feature_selection — variable selectors

Method	Fully-qualified name	Namespace	Refs
correlation	n4m.feature_selection.filter.correlation	n4m.feature_selection.filter	C
variance	n4m.feature_selection.filter.variance	n4m.feature_selection.filter	C
interval	n4m.feature_selection.interval.interval	n4m.feature_selection.interval	C
variable_select	n4m.feature_selection.ranking.variable_select	n4m.feature_selection.ranking	C
bipls	n4m.feature_selection.wrapper.bipls	n4m.feature_selection.wrapper	C
bve	n4m.feature_selection.wrapper.bve	n4m.feature_selection.wrapper	C
cars	n4m.feature_selection.wrapper.cars	n4m.feature_selection.wrapper	C
emcuve	n4m.feature_selection.wrapper.emcuve	n4m.feature_selection.wrapper	C
ga	n4m.feature_selection.wrapper.ga	n4m.feature_selection.wrapper	C
ipw	n4m.feature_selection.wrapper.ipw	n4m.feature_selection.wrapper	C
irf	n4m.feature_selection.wrapper.irf	n4m.feature_selection.wrapper	C
iriv	n4m.feature_selection.wrapper.iriv	n4m.feature_selection.wrapper	C
pso	n4m.feature_selection.wrapper.pso	n4m.feature_selection.wrapper	C
random_frog	n4m.feature_selection.wrapper.random_frog	n4m.feature_selection.wrapper	C
randomization	n4m.feature_selection.wrapper.randomization	n4m.feature_selection.wrapper	C
rep	n4m.feature_selection.wrapper.rep	n4m.feature_selection.wrapper	C
scars	n4m.feature_selection.wrapper.scars	n4m.feature_selection.wrapper	C
shaving	n4m.feature_selection.wrapper.shaving	n4m.feature_selection.wrapper	C
sipls	n4m.feature_selection.wrapper.sipls	n4m.feature_selection.wrapper	C
spa	n4m.feature_selection.wrapper.spa	n4m.feature_selection.wrapper	C
st	n4m.feature_selection.wrapper.st	n4m.feature_selection.wrapper	C
stability	n4m.feature_selection.wrapper.stability	n4m.feature_selection.wrapper	C
t2	n4m.feature_selection.wrapper.t2	n4m.feature_selection.wrapper	C
uve	n4m.feature_selection.wrapper.uve	n4m.feature_selection.wrapper	C
vip_spa	n4m.feature_selection.wrapper.vip_spa	n4m.feature_selection.wrapper	C
vissa	n4m.feature_selection.wrapper.vissa	n4m.feature_selection.wrapper	C
wvc	n4m.feature_selection.wrapper.wvc	n4m.feature_selection.wrapper	C
wvc_threshold	n4m.feature_selection.wrapper.wvc_threshold	n4m.feature_selection.wrapper	C

model_selection — splitters, AOM search/campaign, sweep

Method	Fully-qualified name	Namespace	Refs
aom_chain_screen_refit	n4m.model_selection.aom_campaign.aom_chain_screen_refit	n4m.model_selection.aom_campaign	C, Py
aom_staged_chain_campaign	n4m.model_selection.aom_campaign.aom_staged_chain_campaign	n4m.model_selection.aom_campaign	C, Py
aom_chain_fixed_fit	n4m.model_selection.aom_search.aom_chain_fixed_fit	n4m.model_selection.aom_search	C, Py
aom_chain_ridge_pls	n4m.model_selection.aom_search.aom_chain_ridge_pls	n4m.model_selection.aom_search	C, Py
aom_chain_sweep	n4m.model_selection.aom_search.aom_chain_sweep	n4m.model_selection.aom_search	C, Py
aom_pls	n4m.model_selection.aom_search.aom_pls	n4m.model_selection.aom_search	C, Py
aom_preprocessing	n4m.model_selection.aom_search.aom_preprocessing	n4m.model_selection.aom_search	C, Py
aom_sweep	n4m.model_selection.aom_search.aom_sweep	n4m.model_selection.aom_search	C, Py
pop_pls	n4m.model_selection.aom_search.pop_pls	n4m.model_selection.aom_search	C, Py
ridge_global	n4m.model_selection.aom_search.ridge_global	n4m.model_selection.aom_search	C, Py
robust_hpo	n4m.model_selection.aom_search.robust_hpo	n4m.model_selection.aom_search	C, Py
binned_strat_group_kfold	n4m.model_selection.splitters.binned_strat_group_kfold	n4m.model_selection.splitters	C
data_twinning	n4m.model_selection.splitters.data_twinning	n4m.model_selection.splitters	C
kbins_stratified	n4m.model_selection.splitters.kbins_stratified	n4m.model_selection.splitters	C
kennard_stone	n4m.model_selection.splitters.kennard_stone	n4m.model_selection.splitters	C
kmeans	n4m.model_selection.splitters.kmeans	n4m.model_selection.splitters	C
spxy	n4m.model_selection.splitters.spxy	n4m.model_selection.splitters	C
spxy_fold	n4m.model_selection.splitters.spxy_fold	n4m.model_selection.splitters	C
spxy_g_fold	n4m.model_selection.splitters.spxy_g_fold	n4m.model_selection.splitters	C
systematic_circular	n4m.model_selection.splitters.systematic_circular	n4m.model_selection.splitters	C
sweep	n4m.model_selection.sweep.sweep	n4m.model_selection.sweep	C, Py

domain_adaptation — calibration transfer / standardization

Method	Fully-qualified name	Namespace	Refs
di_pls	n4m.domain_adaptation.invariant.di_pls	n4m.domain_adaptation.invariant	C
transfer_metrics	n4m.domain_adaptation.metrics.transfer_metrics	n4m.domain_adaptation.metrics	C
epo	n4m.domain_adaptation.orthogonalization.epo	n4m.domain_adaptation.orthogonalization	C
direct_standardization	n4m.domain_adaptation.standardization.direct_standardization	n4m.domain_adaptation.standardization	C
ds	n4m.domain_adaptation.standardization.ds	n4m.domain_adaptation.standardization	C
pds	n4m.domain_adaptation.standardization.pds	n4m.domain_adaptation.standardization	C
piecewise_direct_standardization	n4m.domain_adaptation.standardization.piecewise_direct_standardization	n4m.domain_adaptation.standardization	C
robust_direct_standardization	n4m.domain_adaptation.standardization.robust_direct_standardization	n4m.domain_adaptation.standardization	C
slope_bias	n4m.domain_adaptation.standardization.slope_bias	n4m.domain_adaptation.standardization	C

outlier_detection — sample-level screeners + Q/T²

Method	Fully-qualified name	Namespace	Refs
composite	n4m.outlier_detection.composite	n4m.outlier_detection	C
high_leverage	n4m.outlier_detection.high_leverage	n4m.outlier_detection	C
hotelling_t2	n4m.outlier_detection.hotelling_t2	n4m.outlier_detection	C
q_residuals	n4m.outlier_detection.q_residuals	n4m.outlier_detection	C
spectral_quality	n4m.outlier_detection.spectral_quality	n4m.outlier_detection	C
x_outlier	n4m.outlier_detection.x_outlier	n4m.outlier_detection	C
y_outlier	n4m.outlier_detection.y_outlier	n4m.outlier_detection	C

ensemble — bagging / boosting / stacking / AOM blenders

Method	Fully-qualified name	Namespace	Refs
aom_operator_pls_stack	n4m.ensemble.aom_operator_pls_stack	n4m.ensemble	C, Py
aom_ridge_blender	n4m.ensemble.aom_ridge_blender	n4m.ensemble	C, Py
bagging_pls	n4m.ensemble.bagging_pls	n4m.ensemble	C
boosting_pls	n4m.ensemble.boosting_pls	n4m.ensemble	C
moment_stack	n4m.ensemble.moment_stack	n4m.ensemble	C, Py
random_subspace_pls	n4m.ensemble.random_subspace_pls	n4m.ensemble	C

compose — AOM operator superblocks

Method	Fully-qualified name	Namespace	Refs
aom_pls_superblock	n4m.compose.aom_superblock.aom_pls_superblock	n4m.compose.aom_superblock	C, Py
aom_ridge_pls_superblock	n4m.compose.aom_superblock.aom_ridge_pls_superblock	n4m.compose.aom_superblock	C, Py
ridge_active_superblock	n4m.compose.aom_superblock.ridge_active_superblock	n4m.compose.aom_superblock	C, Py
ridge_mkl_superblock	n4m.compose.aom_superblock.ridge_mkl_superblock	n4m.compose.aom_superblock	C, Py
ridge_superblock	n4m.compose.aom_superblock.ridge_superblock	n4m.compose.aom_superblock	C, Py

metrics — scoring + diagnostics

Method	Fully-qualified name	Namespace	Refs
pls_diagnostics	n4m.metrics.diagnostics.pls_diagnostics	n4m.metrics.diagnostics	C
pls_monitoring	n4m.metrics.diagnostics.pls_monitoring	n4m.metrics.diagnostics	C
approximate_press	n4m.metrics.scoring.approximate_press	n4m.metrics.scoring	C
one_se_rule	n4m.metrics.scoring.one_se_rule	n4m.metrics.scoring	C
regression_metrics	n4m.metrics.scoring.regression_metrics	n4m.metrics.scoring	C

decomposition — flexible PCA / SVD

Method	Fully-qualified name	Namespace	Refs
flexible_pca	n4m.decomposition.flexible_pca	n4m.decomposition	C
flexible_svd	n4m.decomposition.flexible_svd	n4m.decomposition	C

lowlevel — sufficient-statistics substrate

Method	Fully-qualified name	Namespace	Refs
moments	n4m.lowlevel.moments.moments	n4m.lowlevel.moments	C, Py

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See the benchmark overview for how parity and timing are measured, and the GitHub Pages dashboard for an interactive cross-method comparison. The ABI 2.0 namespace migration is documented in the ABI-2 migration guide.