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 |