Smithsonian             Smithsonian Museums
add_step                Add a New Operation to the Current Recipe
bake                    Apply a Trained Data Recipe
biomass                 Biomass Data
check_cols              Check if all Columns are Present
check_missing           Check for Missing Values
check_range             Check Range Consistency
covers                  Raw Cover Type Data
credit_data             Credit Data
detect_step             Detect if a particular step or check is used in
                        a recipe
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 Finalized Training Set
names0                  Naming Tools
okc                     OkCupid Data
prep                    Train a Data Recipe
prepper                 Wrapper function for preparing recipes within
                        resampling
print.recipe            Print a Recipe
recipe                  Create a Recipe for Preprocessing Data
recipes                 recipes: A package for computing and
                        preprocessing design matrices.
roles                   Manually Alter Roles
selections              Methods for Select 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_bagimpute          Imputation via Bagged Trees
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_corr               High Correlation Filter
step_count              Create Counts of Patterns using Regular
                        Expressions
step_date               Date Feature Generator
step_depth              Data Depths
step_discretize         Discretize Numeric Variables
step_downsample         Down-Sample a Data Set Based on a Factor
                        Variable
step_dummy              Dummy Variables Creation
step_factor2string      Convert Factors to Strings
step_filter             Filter rows using dplyr
step_geodist            Distance between two locations
step_holiday            Holiday Feature Generator
step_hyperbolic         Hyperbolic Transformations
step_ica                ICA Signal Extraction
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_knnimpute          Imputation via K-Nearest Neighbors
step_kpca               Kernel PCA Signal Extraction
step_lag                Create a lagged predictor
step_lincomb            Linear Combination Filter
step_log                Logarithmic Transformation
step_logit              Logit Transformation
step_lowerimpute        Impute Numeric Data Below the Threshold of
                        Measurement
step_meanimpute         Impute Numeric Data Using the Mean
step_medianimpute       Impute Numeric Data Using the Median
step_modeimpute         Impute Nominal Data Using the Most Common Value
step_mutate             Add new variables using 'mutate'
step_naomit             Remove observations with missing values
step_nnmf               NNMF Signal Extraction
step_novel              Simple Value Assignments for Novel Factor
                        Levels
step_ns                 Nature 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_pls                Partial Least Squares Feature Extraction
step_poly               Orthogonal Polynomial Basis Functions
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              Create Dummy Variables using Regular
                        Expressions
step_relu               Apply (Smoothed) Rectified Linear
                        Transformation
step_rm                 General Variable Filter
step_rollimpute         Impute Numeric Data Using a Rolling Window
                        Statistic
step_sample             Sample rows using dplyr
step_scale              Scaling Numeric Data
step_shuffle            Shuffle Variables
step_slice              Filter rows by position using dplyr
step_spatialsign        Spatial Sign Preprocessing
step_sqrt               Square Root Transformation
step_string2factor      Convert Strings to Factors
step_unorder            Convert Ordered Factors to Unordered Factors
step_upsample           Up-Sample a Data Set Based on a Factor Variable
step_window             Moving Window Functions
step_zv                 Zero Variance Filter
summary.recipe          Summarize a Recipe
terms_select            Select Terms in a Step Function.
tidy.recipe             Tidy the Result of a Recipe
update.step             Update a recipe step
