BinomialOutcomeTreatment
                        Stateful object for designing and applying
                        binomial outcome treatments.
MultinomialOutcomeTreatment
                        Stateful object for designing and applying
                        multinomial outcome treatments.
NumericOutcomeTreatment
                        Stateful object for designing and applying
                        numeric outcome treatments.
UnsupervisedTreatment   Stateful object for designing and applying
                        unsupervised treatments.
apply_transform         Transform second argument by first.
as_rquery_plan          Convert vtreatment plans into a sequence of
                        rquery operations.
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.
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.
multinomial_parameters
                        vtreat multinomial parameters.
novel_value_summary     Report new/novel appearances of character
                        values.
oneWayHoldout           One way holdout, a splitFunction in the sense
                        of vtreat::buildEvalSets.
patch_columns_into_frame
                        Patch columns into data.frame.
pre_comp_xval           Pre-computed cross-plan (so same split happens
                        each time).
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.
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.
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-package          vtreat: A Statistically Sound 'data.frame'
                        Processor/Conditioner
