.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_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
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               Non-Negative Matrix Factorization Signal
                        Extraction
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 Some 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
