Merge pull request #192 from tidymodels/tidy-descriptions

R/collapse_cart.R

@@ -1,6 +1,6 @@
 #' Supervised Collapsing of Factor Levels
 #'
-#' `step_collapse_cart` creates a *specification* of a recipe step that can
+#' `step_collapse_cart()` creates a *specification* of a recipe step that can
 #' collapse factor levels into a smaller set using a supervised tree.
 #'
 #' @param recipe A recipe object. The step will be added to the sequence of

R/collapse_stringdist.R

@@ -1,6 +1,6 @@
 #' collapse factor levels using stringdist
 #'
-#' `step_collapse_stringdist` creates a *specification* of a recipe step that
+#' `step_collapse_stringdist()` creates a *specification* of a recipe step that
 #' will collapse factor levels that have a low stringdist between them.
 #'
 #' @inheritParams recipes::step_center

R/discretize_cart.R

@@ -1,6 +1,6 @@
 #' Discretize numeric variables with CART
 #'
-#' `step_discretize_cart` creates a *specification* of a recipe step that will
+#' `step_discretize_cart()` creates a *specification* of a recipe step that will
 #' discretize numeric data (e.g. integers or doubles) into bins in a supervised
 #' way using a CART model.
 #'

R/discretize_xgb.R

@@ -1,6 +1,6 @@
 #' Discretize numeric variables with XgBoost
 #'
-#' `step_discretize_xgb` creates a *specification* of a recipe step that will
+#' `step_discretize_xgb()` creates a *specification* of a recipe step that will
 #' discretize numeric data (e.g. integers or doubles) into bins in a supervised
 #' way using an XgBoost model.
 #'

R/embed.R

@@ -1,10 +1,10 @@
 #' Encoding Factors into Multiple Columns
 #'
-#' `step_embed` creates a *specification* of a recipe step that will convert a
+#' `step_embed()` creates a *specification* of a recipe step that will convert a
 #' nominal (i.e. factor) predictor into a set of scores derived from a
 #' tensorflow model via a word-embedding model. `embed_control` is a simple
 #' wrapper for setting default options.
-#'
+#' 
 #' @param recipe A recipe object. The step will be added to the sequence of
 #'   operations for this recipe.
 #' @param ... One or more selector functions to choose variables. For

R/feature_hash.R

@@ -2,7 +2,7 @@
 #'
 #' @description `r lifecycle::badge("soft-deprecated")`
 #'
-#'   `step_feature_hash` is being deprecated in favor of
+#'   `step_feature_hash()` is being deprecated in favor of
 #'   [textrecipes::step_dummy_hash()]. This function creates a *specification*
 #'   of a recipe step that will convert nominal data (e.g. character or factors)
 #'   into one or more numeric binary columns using the levels of the original

R/lencode_bayes.R

@@ -1,7 +1,7 @@
 #' Supervised Factor Conversions into Linear Functions using Bayesian Likelihood
 #' Encodings
 #'
-#' `step_lencode_bayes` creates a *specification* of a recipe step that will
+#' `step_lencode_bayes()` creates a *specification* of a recipe step that will
 #' convert a nominal (i.e. factor) predictor into a single set of scores derived
 #' from a generalized linear model estimated using Bayesian analysis.
 #'

R/lencode_glm.R

@@ -1,7 +1,7 @@
 #' Supervised Factor Conversions into Linear Functions using Likelihood
 #' Encodings
 #'
-#' `step_lencode_glm` creates a *specification* of a recipe step that will
+#' `step_lencode_glm()` creates a *specification* of a recipe step that will
 #' convert a nominal (i.e. factor) predictor into a single set of scores derived
 #' from a generalized linear model.
 #'

R/lencode_mixed.R

@@ -1,7 +1,7 @@
 #' Supervised Factor Conversions into Linear Functions using Bayesian Likelihood
 #' Encodings
 #'
-#' `step_lencode_mixed` creates a *specification* of a recipe step that will
+#' `step_lencode_mixed()` creates a *specification* of a recipe step that will
 #' convert a nominal (i.e. factor) predictor into a single set of scores derived
 #' from a generalized linear mixed model.
 #'

R/pca_truncated.R

@@ -1,6 +1,6 @@
 #' Truncated PCA Signal Extraction
 #'
-#' `step_pca_truncated` creates a *specification* of a recipe step that will
+#' `step_pca_truncated()` creates a *specification* of a recipe step that will
 #' convert numeric data into one or more principal components. It is truncated
 #' as it only calculates the number of components it is asked instead of all of
 #' them as is done in [recipes::step_pca()].

R/umap.R

@@ -1,7 +1,7 @@
 #' Supervised and unsupervised uniform manifold approximation and projection
 #' (UMAP)
 #'
-#' `step_umap` creates a *specification* of a recipe step that will project a
+#' `step_umap()` creates a *specification* of a recipe step that will project a
 #' set of features into a smaller space.
 #'
 #' @inheritParams recipes::step_pca

R/woe.R

@@ -1,6 +1,6 @@
 #' Weight of evidence transformation
 #'
-#' `step_woe` creates a *specification* of a recipe step that will transform
+#' `step_woe()` creates a *specification* of a recipe step that will transform
 #' nominal data into its numerical transformation based on weights of evidence
 #' against a binary outcome.
 #'