Preprocessing Tools to Create Design Matrices


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Documentation for package ‘recipes’ version 0.1.0

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recipes-package recipes: A package for computing and preprocessing design matrices.
add_role Manually Add Roles
add_step Add a New Step to Current Recipe
all_nominal Role Selection
all_numeric Role Selection
all_outcomes Role Selection
all_predictors Role Selection
bake Apply a Trained Data Recipe
bake.recipe Apply a Trained Data Recipe
biomass Biomass Data
covers Raw Cover Type Data
credit_data Credit Data
current_info Role Selection
denom_vars Ratio Variable Creation
discretize Discretize Numeric Variables
discretize.default Discretize Numeric Variables
discretize.numeric Discretize Numeric Variables
has_role Role Selection
has_type Role Selection
imp_vars Imputation via Bagged Trees
juice Extract Finalized Training Set
names0 Sequences of Names with Padded Zeros
okc OkCupid Data
predict.discretize Discretize Numeric Variables
prep Train a Data Recipe
prep.recipe Train a Data Recipe
print.recipe Print a Recipe
recipe Create a Recipe for Preprocessing Data
recipe.data.frame Create a Recipe for Preprocessing Data
recipe.default Create a Recipe for Preprocessing Data
recipe.formula Create a Recipe for Preprocessing Data
recipe.matrix Create a Recipe for Preprocessing Data
recipes recipes: A package for computing and preprocessing design matrices.
selections Methods for Select Variables in Step Functions
step A General Step Wrapper
step_bagimpute Imputation via Bagged Trees
step_bin2factor Create a Factors from A Dummy Variable
step_BoxCox Box-Cox Transformation for Non-Negative Data
step_center Centering Numeric Data
step_classdist Distances to Class Centroids
step_corr High Correlation Filter
step_date Date Feature Generator
step_depth Data Depths
step_discretize Discretize Numeric Variables
step_dummy Dummy Variables Creation
step_holiday Holiday Feature Generator
step_hyperbolic Hyperbolic Transformations
step_ica ICA Signal Extraction
step_interact Create Interaction Variables
step_intercept Add intercept (or constant) column
step_invlogit Inverse Logit Transformation
step_isomap Isomap Embedding
step_knnimpute Imputation via K-Nearest Neighbors
step_kpca Kernel PCA Signal Extraction
step_lincomb Linear Combination Filter
step_log Logarithmic Transformation
step_logit Logit Transformation
step_meanimpute Impute Numeric Data Using the Mean
step_modeimpute Impute Nominal Data Using the Most Common Value
step_ns Nature Spline Basis Functions
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_poly Orthogonal Polynomial Basis Functions
step_range Scaling Numeric Data to a Specific Range
step_ratio Ratio Variable Creation
step_regex Create Dummy Variables using Regular Expressions
step_rm General Variable Filter
step_scale Scaling Numeric Data
step_shuffle Shuffle Variables
step_spatialsign Spatial Sign Preprocessing
step_sqrt Square Root Transformation
step_window Moving Window Functions
step_YeoJohnson Yeo-Johnson Transformation
summary.recipe Summarize a Recipe
terms_select Select Terms in a Step Function.