Man pages for 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... |
| BinomialOutcomeTreatment | Stateful object for designing and applying binomial outcome... |
| buildEvalSets | Build set carve-up for out-of sample evaluation. |
| center_scale | Center and scale a set of variables. |
| classification_parameters | vtreat classification parameters. |
| design_missingness_treatment | Design a simple treatment plan to indicate missingingness and... |
| designTreatmentsC | Build all treatments for a data frame to predict a... |
| designTreatmentsN | build all treatments for a data frame to predict a numeric... |
| designTreatmentsZ | Design variable treatments with no outcome variable. |
| dot-wmean | Compute weighted mean |
| 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. |
| flatten_fn_list | Flatten a list of functions onto d. |
| format.vtreatment | Display treatment plan. |
| get_feature_names | Return feasible feature names. |
| get_score_frame | Return score frame from vps. |
| getSplitPlanAppLabels | read application labels off a split plan. |
| get_transform | Return underlying transform from vps. |
| kWayCrossValidation | k-fold cross validation, a splitFunction in the sense of... |
| kWayStratifiedY | k-fold cross validation stratified on y, a splitFunction in... |
| kWayStratifiedYReplace | k-fold cross validation stratified with replacement on y, a... |
| makeCustomCoderCat | Make a categorical input custom coder. |
| makeCustomCoderNum | Make a numeric input custom coder. |
| makekWayCrossValidationGroupedByColumn | Build a k-fold cross validation splitter, respecting (never... |
| mkCrossFrameCExperiment | Run categorical cross-frame experiment. |
| mkCrossFrameMExperiment | Function to build multi-outcome vtreat cross frame and... |
| mkCrossFrameNExperiment | Run a numeric cross frame experiment. |
| MultinomialOutcomeTreatment | Stateful object for designing and applying multinomial... |
| multinomial_parameters | vtreat multinomial parameters. |
| novel_value_summary | Report new/novel appearances of character values. |
| NumericOutcomeTreatment | Stateful object for designing and applying numeric outcome... |
| oneWayHoldout | One way holdout, a splitFunction in the sense of... |
| patch_columns_into_frame | Patch columns into data.frame. |
| 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... |
| regression_parameters | vtreat regression parameters. |
| rqdatatable_prepare | Apply a treatment plan using rqdatatable. |
| 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. |
| unsupervised_parameters | vtreat unsupervised parameters. |
| UnsupervisedTreatment | Stateful object for designing and applying unsupervised... |
| 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$treatment... |
| vorig | Original variable name from a treatmentplan$treatment item. |
| vtreat-package | vtreat: A Statistically Sound 'data.frame'... |
