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