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

## Documentation for package ‘vtreat’ version 1.3.8

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

vtreat-package | vtreat: A Statistically Sound 'data.frame' Processor/Conditioner
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.
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.
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.
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
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