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.
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.
format.vtreatment       Display treatment plan.
getSplitPlanAppLabels   read application labels off a split plan.
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 .
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.
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.
ppCoderC                Solve a categorical partial pooling problem.
ppCoderN                Solve a numeric partial pooling problem.
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
rquery_prepare          Materialize a treated data frame remotely.
run_vtreat_tests        Run vtreat tests.
solveIsotone            Solve for best single-direction (non-decreasing
                        or non-increasing) fit.
solveNonDecreasing      Solve for best non-decreasing fit using isotone
                        regression (from the "isotone" package <URL:
                        https://CRAN.R-project.org/package=isotone>).
solveNonIncreasing      Solve for best non-increasing fit.
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.
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
