| 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 |