Check for New Values
Check Range Consistency
Helpers for printing step functions
Add a New Operation to the Current Recipe
Apply a Trained Data Recipe
Helper Functions for Profile Data Sets
Discretize Numeric Variables
recipes: A package for computing and preprocessing design matrices.
Create a Recipe for Preprocessing Data
Create a Formula from a Prepared Recipe
Check for Missing Values
Extract Finalized Training Set
check that newly created variable names don't overlap
Naming Tools
Update packages
Yeo-Johnson Transformation
Distances to Class Centroids
Filter rows using dplyr
Impute Numeric Data Below the Threshold of Measurement
Distance between two locations
High Correlation Filter
Check if all Columns are Present
Wrapper function for preparing recipes within resampling
Check Variable Class
step
sets the class of the step
and check
is for checks.
Impute Numeric Data Using the Mean
Internal Functions
Box-Cox Transformation for Non-Negative Data
Manually Alter Roles
Train a Data Recipe
Methods for Select Variables in Step Functions
Remove observations with missing values
Add intercept (or constant) column
Discretize Numeric Variables
Polynomial Kernel PCA Signal Extraction
Sort rows using dplyr
Radial Basis Function Kernel PCA Signal Extraction
Down-Sample a Data Set Based on a Factor Variable
Inverse Transformation
Center and scale numeric data
Simple Value Assignments for Novel Factor Levels
NNMF Signal Extraction
Convert Factors to Strings
Holiday Feature Generator
Dummy Variables Creation
Apply (Smoothed) Rectified Linear Transformation
PCA Signal Extraction
Update a recipe step
Relevel factors to a desired level
Collapse Some Categorical Levels
Sample rows using dplyr
Imputation via Bagged Trees
Detect if a particular step or check is used in a recipe
Role Selection
Check to see if a recipe is trained/prepared
Quantitatively check on variables
Create a lagged predictor
Isomap Embedding
Hyperbolic Transformations
Inverse Logit Transformation
Create a Factors from A Dummy Variable
Logarithmic Transformation
Logit Transformation
Add new variables using mutate
Scaling Numeric Data
Partial Least Squares Feature Extraction
General Variable Filter
Up-Sample a Data Set Based on a Factor Variable
Convert Ordered Factors to Unordered Factors
Orthogonal Polynomial Basis Functions
Impute Numeric Data Using a Rolling Window Statistic
Linear Combination Filter
Mutate multiple columns
Natural Spline Basis Functions
Spatial Sign Preprocessing
Convert Numbers to Factors
Objects exported from other packages
S3 methods for tracking which additional packages are needed for steps.
Select Terms in a Step Function.
Summarize a Recipe
Create Dummy Variables using Regular Expressions
Ratio Variable Creation
Print a Recipe
B-Spline Basis Functions
Make a random identification field for steps
Square Root Transformation
Date Feature Generator
Centering numeric data
Data Depths
Imputation of numeric variables via a linear model.
Impute Numeric Data Using the Median
ICA Signal Extraction
Cut a numeric variable into a factor
Create Counts of Patterns using Regular Expressions
Convert values to predefined integers
Imputation via K-Nearest Neighbors
Create Interaction Variables
Kernel PCA Signal Extraction
Create a Profiling Version of a Data Set
Near-Zero Variance Filter
Impute Nominal Data Using the Most Common Value
Convert Ordinal Factors to Numeric Scores
Rename variables by name
Scaling Numeric Data to a Specific Range
Filter rows by position using dplyr
Rename multiple columns
Shuffle Variables
Convert Strings to Factors
Assign missing categories to "unknown"
Zero Variance Filter
Tidy the Result of a Recipe
tunable methods for recipes
Moving Window Functions