A Statistically Sound 'data.frame' Processor/Conditioner

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Documentation for package ‘vtreat’ version 1.6.5

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

vtreat-package	vtreat: A Statistically Sound 'data.frame' Processor/Conditioner
apply_transform	Transform second argument by first.
as_rquery_plan	Convert vtreatment plans into a sequence of rquery operations.
BinomialOutcomeTreatment	Stateful object for designing and applying binomial outcome treatments.
buildEvalSets	Build set carve-up for out-of sample evaluation.
center_scale	Center and scale a set of variables.
classification_parameters	vtreat classification parameters.
designTreatmentsC	Build all treatments for a data frame to predict a categorical outcome.
designTreatmentsN	build all treatments for a data frame to predict a numeric outcome
designTreatmentsZ	Design variable treatments with no outcome variable.
design_missingness_treatment	Design a simple treatment plan to indicate missingingness and perform simple imputation.
fit	Fit first arguemnt to data in second argument.
fit_prepare	Fit and prepare in a cross-validated manner.
fit_transform	Fit and transform in a cross-validated manner.
format.vtreatment	Display treatment plan.
getSplitPlanAppLabels	read application labels off a split plan.
get_feature_names	Return feasible feature names.
get_score_frame	Return score frame from vps.
get_transform	Return underlying transform from vps.
kWayCrossValidation	k-fold cross validation, a splitFunction in the sense of vtreat::buildEvalSets
kWayStratifiedY	k-fold cross validation stratified on y, a splitFunction in the sense of vtreat::buildEvalSets
kWayStratifiedYReplace	k-fold cross validation stratified with replacement on y, a splitFunction in the sense of vtreat::buildEvalSets .
makeCustomCoderCat	Make a categorical input custom coder.
makeCustomCoderNum	Make a numeric input custom coder.
makekWayCrossValidationGroupedByColumn	Build a k-fold cross validation splitter, respecting (never splitting) groupingColumn.
materialize_treated	Materialize a treated data frame remotely.
mkCrossFrameCExperiment	Run categorical cross-frame experiment.
mkCrossFrameMExperiment	Function to build multi-outcome vtreat cross frame and treatment plan.
mkCrossFrameNExperiment	Run a numeric cross frame experiment.
MultinomialOutcomeTreatment	Stateful object for designing and applying multinomial outcome treatments.
multinomial_parameters	vtreat multinomial parameters.
novel_value_summary	Report new/novel appearances of character values.
NumericOutcomeTreatment	Stateful object for designing and applying numeric outcome treatments.
oneWayHoldout	One way holdout, a splitFunction in the sense of vtreat::buildEvalSets.
patch_columns_into_frame	Patch columns into data.frame.
prepare	Apply treatments and restrict to useful variables.
prepare.multinomial_plan	Function to apply mkCrossFrameMExperiment treatemnts.
prepare.simple_plan	Prepare a simple treatment.
prepare.treatmentplan	Apply treatments and restrict to useful variables.
pre_comp_xval	Pre-computed cross-plan (so same split happens each time).
print.multinomial_plan	Print treatmentplan.
print.simple_plan	Print treatmentplan.
print.treatmentplan	Print treatmentplan.
print.vtreatment	Print treatmentplan.
problemAppPlan	check if appPlan is a good carve-up of 1:nRows into nSplits groups
regression_parameters	vtreat regression parameters.
rquery_prepare	Materialize a treated data frame remotely.
solve_piecewise	Solve as piecewise linear problem, numeric target.
solve_piecewisec	Solve as piecewise logit problem, categorical target.
spline_variable	Spline variable numeric target.
spline_variablec	Spline variable categorical target.
square_window	Build a square windows variable, numeric target.
square_windowc	Build a square windows variable, categorical target.
track_values	Track unique character values for variables.
UnsupervisedTreatment	Stateful object for designing and applying unsupervised treatments.
unsupervised_parameters	vtreat unsupervised parameters.
value_variables_C	Value variables for prediction a categorical outcome.
value_variables_N	Value variables for prediction a numeric outcome.
variable_values	Return variable evaluations.
vnames	New treated variable names from a treatmentplan$treatment item.
vorig	Original variable name from a treatmentplan$treatment item.
vtreat	vtreat: A Statistically Sound 'data.frame' Processor/Conditioner