# A Statistically Sound 'data.frame' Processor/Conditioner

## 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