.get_data_types         Get types for use in recipes
add_step                Add a New Operation to the Current Recipe
bake                    Apply a trained preprocessing recipe
case-weight-helpers     Helpers for steps with case weights
case_weights            Using case weights with recipes
check_class             Check variable class
check_cols              Check if all columns are present
check_missing           Check for missing values
check_new_values        Check for new values
check_range             Check range consistency
detect_step             Detect if a particular step or check is used in
                        a recipe
developer_functions     Developer functions for creating recipes steps
discretize              Discretize Numeric Variables
formula.recipe          Create a formula from a prepared recipe
fully_trained           Check to see if a recipe is trained/prepared
has_role                Role Selection
juice                   Extract transformed training set
names0                  Naming Tools
prep                    Estimate a preprocessing recipe
prepper                 Wrapper function for preparing recipes within
                        resampling
print.recipe            Print a Recipe
recipe                  Create a recipe for preprocessing data
recipes_argument_select
                        Evaluate a selection with tidyselect semantics
                        for arguments
recipes_eval_select     Evaluate a selection with tidyselect semantics
                        specific to recipes
recipes_extension_check
                        Checks that steps have all S3 methods
roles                   Manually alter roles
selections              Methods for selecting variables in step
                        functions
sparse_data             Using sparse data with recipes
step_BoxCox             Box-Cox transformation for non-negative data
step_YeoJohnson         Yeo-Johnson transformation
step_arrange            Sort rows using dplyr
step_bin2factor         Create a factors from A dummy variable
step_bs                 B-spline basis functions
step_center             Centering numeric data
step_classdist          Distances to class centroids
step_classdist_shrunken
                        Compute shrunken centroid distances for
                        classification models
step_corr               High correlation filter
step_count              Create counts of patterns using regular
                        expressions
step_cut                Cut a numeric variable into a factor
step_date               Date feature generator
step_depth              Data depths
step_discretize         Discretize Numeric Variables
step_dummy              Create traditional dummy variables
step_dummy_extract      Extract patterns from nominal data
step_dummy_multi_choice
                        Handle levels in multiple predictors together
step_factor2string      Convert factors to strings
step_filter             Filter rows using dplyr
step_filter_missing     Missing value column filter
step_geodist            Distance between two locations
step_harmonic           Add sin and cos terms for harmonic analysis
step_holiday            Holiday feature generator
step_hyperbolic         Hyperbolic transformations
step_ica                ICA signal extraction
step_impute_bag         Impute via bagged trees
step_impute_knn         Impute via k-nearest neighbors
step_impute_linear      Impute numeric variables via a linear model
step_impute_lower       Impute numeric data below the threshold of
                        measurement
step_impute_mean        Impute numeric data using the mean
step_impute_median      Impute numeric data using the median
step_impute_mode        Impute nominal data using the most common value
step_impute_roll        Impute numeric data using a rolling window
                        statistic
step_indicate_na        Create missing data column indicators
step_integer            Convert values to predefined integers
step_interact           Create interaction variables
step_intercept          Add intercept (or constant) column
step_inverse            Inverse transformation
step_invlogit           Inverse logit transformation
step_isomap             Isomap embedding
step_kpca               Kernel PCA signal extraction
step_kpca_poly          Polynomial kernel PCA signal extraction
step_kpca_rbf           Radial basis function kernel PCA signal
                        extraction
step_lag                Create a lagged predictor
step_lincomb            Linear combination filter
step_log                Logarithmic transformation
step_logit              Logit transformation
step_mutate             Add new variables using dplyr
step_mutate_at          Mutate multiple columns using dplyr
step_naomit             Remove observations with missing values
step_nnmf_sparse        Non-negative matrix factorization signal
                        extraction with lasso penalization
step_normalize          Center and scale numeric data
step_novel              Simple value assignments for novel factor
                        levels
step_ns                 Natural spline basis functions
step_num2factor         Convert numbers to factors
step_nzv                Near-zero variance filter
step_ordinalscore       Convert ordinal factors to numeric scores
step_other              Collapse infrequent categorical levels
step_pca                PCA signal extraction
step_percentile         Percentile transformation
step_pls                Partial least squares feature extraction
step_poly               Orthogonal polynomial basis functions
step_poly_bernstein     Generalized bernstein polynomial basis
step_profile            Create a profiling version of a data set
step_range              Scaling numeric data to a specific range
step_ratio              Ratio variable creation
step_regex              Detect a regular expression
step_relevel            Relevel factors to a desired level
step_relu               Apply (smoothed) rectified linear
                        transformation
step_rename             Rename variables by name using dplyr
step_rename_at          Rename multiple columns using dplyr
step_rm                 General variable filter
step_sample             Sample rows using dplyr
step_scale              Scaling numeric data
step_select             Select variables using dplyr
step_shuffle            Shuffle variables
step_slice              Filter rows by position using dplyr
step_spatialsign        Spatial sign preprocessing
step_spline_b           Basis splines
step_spline_convex      Convex splines
step_spline_monotone    Monotone splines
step_spline_natural     Natural splines
step_spline_nonnegative
                        Non-negative splines
step_sqrt               Square root transformation
step_string2factor      Convert strings to factors
step_time               Time feature generator
step_unknown            Assign missing categories to "unknown"
step_unorder            Convert ordered factors to unordered factors
step_window             Moving window functions
step_zv                 Zero variance filter
summary.recipe          Summarize a recipe
tidy.step_BoxCox        Tidy the result of a recipe
update.step             Update a recipe step
update_role_requirements
                        Update role specific requirements
