All functions

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.

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

regression_parameters()

vtreat regression parameters.

rquery_prepare() materialize_treated()

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 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.

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