vtreat-package | vtreat: a package for simple variable treatment |
buildEvalSets | Build set partition for out-of sample evaluation. |
catScore | return significnace 1 variable logistic regression |
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. |
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 |
linScore | Return in-sample linear stats and scaling. |
makekWayCrossValidationGroupedByColumn | Build a k-fold cross validation splitter, respecting (never splitting) groupingColumn. |
makekWayCrossValidationOrderedByColumn | Build a k-fold cross validation splitter, respecting (train always above test) orderColumn |
mkCrossFrameCExperiment | Run categorical cross-frame experiment. |
mkCrossFrameNExperiment | Run numeric cross frame experiment. |
oneWayHoldout | One way holdout, a splitFunction in the sense of vtreat::buildEvalSets. Doesn't respect nSplits. |
prepare | Apply treatments and restrict to useful variables. |
print.vtreatment | Print treatmentplan. |
problemAppPlan | check if appPlan is a good partition of 1:nRows into nSplits groups |
vnames | New treated variable names from a treatmentplan$treatment item. |
vorig | Original variable name from a treatmentplan$treatment item. |
vtreat | vtreat: a package for simple variable treatment |