Merge pull request #1207 from tidymodels/title-sentence-case

R/BoxCox.R

@@ -1,4 +1,4 @@
-#' Box-Cox Transformation for Non-Negative Data
+#' Box-Cox transformation for non-negative data
 #'
 #' `step_BoxCox()` creates a *specification* of a recipe step that will transform
 #' data using a Box-Cox transformation.

R/YeoJohnson.R

@@ -1,4 +1,4 @@
-#' Yeo-Johnson Transformation
+#' Yeo-Johnson transformation
 #'
 #' `step_YeoJohnson()` creates a *specification* of a recipe step that will
 #' transform data using a Yeo-Johnson transformation.

R/bin2factor.R

@@ -1,4 +1,4 @@
-#' Create a Factors from A Dummy Variable
+#' Create a factors from A dummy variable
 #'
 #' `step_bin2factor()` creates a *specification* of a recipe step that will
 #' create a two-level factor from a single dummy variable.

R/bs.R

@@ -1,4 +1,4 @@
-#' B-Spline Basis Functions
+#' B-spline basis functions
 #'
 #' `step_bs()` creates a *specification* of a recipe step that will create new
 #' columns that are basis expansions of variables using B-splines.

R/class.R

@@ -1,4 +1,4 @@
-#' Check Variable Class
+#' Check variable class
 #'
 #' `check_class` creates a *specification* of a recipe
 #'  check that will check if a variable is of a designated class.

R/classdist.R

@@ -1,4 +1,4 @@
-#' Distances to Class Centroids
+#' Distances to class centroids
 #'
 #' `step_classdist()` creates a *specification* of a recipe step that will
 #' convert numeric data into Mahalanobis distance measurements to the data

R/colcheck.R

@@ -1,4 +1,4 @@
-#' Check if all Columns are Present
+#' Check if all columns are present
 #'
 #' `check_cols` creates a *specification* of a recipe
 #'  step that will check if all the columns of the training frame are

R/corr.R

@@ -1,4 +1,4 @@
-#' High Correlation Filter
+#' High correlation filter
 #'
 #' `step_corr()` creates a *specification* of a recipe step that will
 #' potentially remove variables that have large absolute correlations with other

R/count.R

@@ -1,4 +1,4 @@
-#' Create Counts of Patterns using Regular Expressions
+#' Create counts of patterns using regular expressions
 #'
 #' `step_count()` creates a *specification* of a recipe step that will create a
 #' variable that counts instances of a regular expression pattern in text.

R/date.R

@@ -1,4 +1,4 @@
-#' Date Feature Generator
+#' Date feature generator
 #'
 #' `step_date()` creates a *specification* of a recipe step that will convert
 #' date data into one or more factor or numeric variables.

R/deprecated-terms_select.R

@@ -1,4 +1,4 @@
-#' Select Terms in a Step Function.
+#' Select terms in a step function.
 #'
 #' @description
 #' `r lifecycle::badge("deprecated")`

R/depth.R

@@ -1,4 +1,4 @@
-#' Data Depths
+#' Data depths
 #'
 #' `step_depth()` creates a *specification* of a recipe step that will convert
 #' numeric data into a measurement of *data depth*. This is done for each value of

R/factor2string.R

@@ -1,4 +1,4 @@
-#' Convert Factors to Strings
+#' Convert factors to strings
 #'
 #' `step_factor2string()` creates a *specification* of a recipe step that will
 #' convert one or more factor vectors to strings.

R/filter_missing.R

@@ -1,4 +1,4 @@
-#' Missing Value Column Filter
+#' Missing value column filter
 #'
 #' `step_filter_missing()` creates a *specification* of a recipe step that will
 #' potentially remove variables that have too many missing values.

R/formula.R

@@ -1,4 +1,4 @@
-#' Create a Formula from a Prepared Recipe
+#' Create a formula from a prepared recipe
 #'
 #' In case a model formula is required, the formula method can
 #'  be used on a recipe to show what predictors and outcome(s)

R/holiday.R

@@ -1,4 +1,4 @@
-#' Holiday Feature Generator
+#' Holiday feature generator
 #'
 #' `step_holiday()` creates a *specification* of a recipe step that will convert
 #' date data into one or more binary indicator variables for common holidays.

R/hyperbolic.R

@@ -1,4 +1,4 @@
-#' Hyperbolic Transformations
+#' Hyperbolic transformations
 #'
 #' `step_hyperbolic()` creates a *specification* of a recipe step that will
 #' transform data using a hyperbolic function.

R/ica.R

@@ -1,4 +1,4 @@
-#' ICA Signal Extraction
+#' ICA signal extraction
 #'
 #' `step_ica()` creates a *specification* of a recipe step that will convert
 #' numeric data into one or more independent components.

R/indicate_na.R

@@ -1,4 +1,4 @@
-#' Create Missing Data Column Indicators
+#' Create missing data column indicators
 #'
 #' `step_indicate_na()` creates a *specification* of a recipe step that will
 #' create and append additional binary columns to the data set to indicate which

R/interact.R

@@ -1,4 +1,4 @@
-#' Create Interaction Variables
+#' Create interaction variables
 #'
 #' `step_interact()` creates a *specification* of a recipe step that will create
 #' new columns that are interaction terms between two or more variables.

R/inverse.R

@@ -1,4 +1,4 @@
-#' Inverse Transformation
+#' Inverse transformation
 #'
 #' `step_inverse()` creates a *specification* of a recipe step that will inverse
 #' transform the data.

R/invlogit.R

@@ -1,4 +1,4 @@
-#' Inverse Logit Transformation
+#' Inverse logit transformation
 #'
 #' `step_invlogit()` creates a *specification* of a recipe step that will
 #' transform the data from real values to be between zero and one.

R/isomap.R

@@ -1,4 +1,4 @@
-#' Isomap Embedding
+#' Isomap embedding
 #'
 #' `step_isomap()` creates a *specification* of a recipe step that uses
 #' multidimensional scaling to convert numeric data into one or more new

R/kpca.R

@@ -1,4 +1,4 @@
-#' Kernel PCA Signal Extraction
+#' Kernel PCA signal extraction
 #'
 #' `step_kpca()` creates a *specification* of a recipe step that will convert
 #' numeric data into one or more principal components using a kernel basis

R/kpca_poly.R

@@ -1,4 +1,4 @@
-#' Polynomial Kernel PCA Signal Extraction
+#' Polynomial kernel PCA signal extraction
 #'
 #' `step_kpca_poly()` creates a *specification* of a recipe step that will
 #' convert numeric data into one or more principal components using a polynomial

R/kpca_rbf.R

@@ -1,4 +1,4 @@
-#' Radial Basis Function Kernel PCA Signal Extraction
+#' Radial basis function kernel PCA signal extraction
 #'
 #' `step_kpca_rbf()` creates a *specification* of a recipe step that will
 #' convert numeric data into one or more principal components using a radial

R/lincomb.R

@@ -1,4 +1,4 @@
-#' Linear Combination Filter
+#' Linear combination filter
 #'
 #' `step_lincomb()` creates a *specification* of a recipe step that will
 #' potentially remove numeric variables that have exact linear combinations

R/log.R

@@ -1,4 +1,4 @@
-#' Logarithmic Transformation
+#' Logarithmic transformation
 #'
 #' `step_log()` creates a *specification* of a recipe step that will log
 #' transform data.

R/logit.R

@@ -1,4 +1,4 @@
-#' Logit Transformation
+#' Logit transformation
 #'
 #' `step_logit()` creates a *specification* of a recipe step that will logit
 #' transform the data.

R/missing.R

@@ -1,4 +1,4 @@
-#' Check for Missing Values
+#' Check for missing values
 #'
 #' `check_missing` creates a *specification* of a recipe
 #'  operation that will check if variables contain missing values.

R/newvalues.R

@@ -1,4 +1,4 @@
-#' Check for New Values
+#' Check for new values
 #'
 #' `check_new_values` creates a *specification* of a recipe
 #'  operation that will check if variables contain new values.

R/nnmf.R

@@ -1,4 +1,4 @@
-#' Non-Negative Matrix Factorization Signal Extraction
+#' Non-negative matrix factorization signal extraction
 #'
 #' @description
 #'

R/nnmf_sparse.R

@@ -1,4 +1,4 @@
-#' Non-Negative Matrix Factorization Signal Extraction with lasso Penalization
+#' Non-negative matrix factorization signal extraction with lasso penalization
 #'
 #' `step_nnmf_sparse()` creates a *specification* of a recipe step that will
 #' convert numeric data into one or more non-negative components.

R/novel.R

@@ -1,4 +1,4 @@
-#' Simple Value Assignments for Novel Factor Levels
+#' Simple value assignments for novel factor levels
 #'
 #' `step_novel()` creates a *specification* of a recipe step that will assign a
 #' previously unseen factor level to `"new"`.

R/ns.R

@@ -1,4 +1,4 @@
-#' Natural Spline Basis Functions
+#' Natural spline basis functions
 #'
 #' `step_ns()` creates a *specification* of a recipe step that will create new
 #' columns that are basis expansions of variables using natural splines.

R/num2factor.R

@@ -1,4 +1,4 @@
-#' Convert Numbers to Factors
+#' Convert numbers to factors
 #'
 #' `step_num2factor()` will convert one or more numeric vectors to factors
 #' (ordered or unordered). This can be useful when categories are encoded as

R/nzv.R

@@ -1,4 +1,4 @@
-#' Near-Zero Variance Filter
+#' Near-zero variance filter
 #'
 #' `step_nzv()` creates a *specification* of a recipe step that will potentially
 #' remove variables that are highly sparse and unbalanced.

R/ordinalscore.R

@@ -1,4 +1,4 @@
-#' Convert Ordinal Factors to Numeric Scores
+#' Convert ordinal factors to numeric scores
 #'
 #' `step_ordinalscore()` creates a *specification* of a recipe step that will
 #' convert ordinal factor variables into numeric scores.

R/other.R

@@ -1,4 +1,4 @@
-#' Collapse Some Categorical Levels
+#' Collapse infrequent categorical levels
 #'
 #' `step_other()` creates a *specification* of a recipe step that will
 #' potentially pool infrequently occurring values into an `"other"` category.

R/pca.R

@@ -1,4 +1,4 @@
-#' PCA Signal Extraction
+#' PCA signal extraction
 #'
 #' `step_pca()` creates a *specification* of a recipe step that will convert
 #' numeric variables into one or more principal components.

R/percentile.R

@@ -1,4 +1,4 @@
-#' Percentile Transformation
+#' Percentile transformation
 #'
 #' `step_percentile()` creates a *specification* of a recipe step that replaces
 #' the value of a variable with its percentile from the training set.

R/pls.R

@@ -1,4 +1,4 @@
-#' Partial Least Squares Feature Extraction
+#' Partial least squares feature extraction
 #'
 #' `step_pls()` creates a *specification* of a recipe step that will convert
 #' numeric data into one or more new dimensions.

R/poly.R

@@ -1,4 +1,4 @@
-#' Orthogonal Polynomial Basis Functions
+#' Orthogonal polynomial basis functions
 #'
 #' `step_poly()` creates a *specification* of a recipe step that will create new
 #' columns that are basis expansions of variables using orthogonal polynomials.

R/poly_bernstein.R

@@ -1,4 +1,4 @@
-#' Generalized Bernstein Polynomial Basis
+#' Generalized bernstein polynomial basis
 #'
 #' `step_poly_bernstein()` creates a *specification* of a recipe step that
 #' creates Bernstein polynomial features.

R/printing.R

@@ -1,4 +1,4 @@
-#' Printing Workhorse Function
+#' Printing workhorse function
 #'
 #' This internal function is used for printing steps.
 #'

R/profile.R

@@ -1,4 +1,4 @@
-#' Create a Profiling Version of a Data Set
+#' Create a profiling version of a data set
 #'
 #' `step_profile()` creates a *specification* of a recipe step that will fix the
 #' levels of all variables but one and will create a sequence of values for the

R/range.R

@@ -1,4 +1,4 @@
-#' Scaling Numeric Data to a Specific Range
+#' Scaling numeric data to a specific range
 #'
 #' `step_range()` creates a *specification* of a recipe step that will normalize
 #' numeric data to be within a pre-defined range of values.

R/range_check.R

@@ -1,4 +1,4 @@
-#' Check Range Consistency
+#' Check range consistency
 #'
 #' `check_range` creates a *specification* of a recipe
 #'  check that will check if the range of a numeric

R/ratio.R

@@ -1,4 +1,4 @@
-#' Ratio Variable Creation
+#' Ratio variable creation
 #'
 #' `step_ratio()` creates a *specification* of a recipe step that will create
 #' one or more ratios from selected numeric variables.

R/relu.R

@@ -1,4 +1,4 @@
-#' Apply (Smoothed) Rectified Linear Transformation
+#' Apply (smoothed) rectified linear transformation
 #'
 #' `step_relu()` creates a *specification* of a recipe step that will add the
 #' rectified linear or softplus transformations of a variable to the data set.

R/rm.R

@@ -1,4 +1,4 @@
-#' General Variable Filter
+#' General variable filter
 #'
 #' `step_rm()` creates a *specification* of a recipe step that will remove
 #' selected variables.

R/roles.R

@@ -1,4 +1,4 @@
-#' Manually Alter Roles
+#' Manually alter roles
 #'
 #' @description
 #' `update_role()` alters an existing role in the recipe or assigns an initial

R/scale.R

@@ -1,4 +1,4 @@
-#' Scaling Numeric Data
+#' Scaling mumeric data
 #'
 #' `step_scale()` creates a *specification* of a recipe step that will normalize
 #' numeric data to have a standard deviation of one.

R/shuffle.R

@@ -1,4 +1,4 @@
-#' Shuffle Variables
+#' Shuffle variables
 #'
 #' `step_shuffle()` creates a *specification* of a recipe step that will
 #' randomly change the order of rows for selected variables.

R/spatialsign.R

@@ -1,4 +1,4 @@
-#' Spatial Sign Preprocessing
+#' Spatial sign preprocessing
 #'
 #' `step_spatialsign()` is a *specification* of a recipe step that will convert
 #' numeric data into a projection on to a unit sphere.

R/spline_b.R

@@ -1,4 +1,4 @@
-#' Basis Splines
+#' Basis splines
 #'
 #' `step_spline_b()` creates a *specification* of a recipe step that creates
 #' b-spline features.

R/spline_convex.R

@@ -1,4 +1,4 @@
-#' Convex Splines
+#' Convex splines
 #'
 #' `step_spline_convex()` creates a *specification* of a recipe step that
 #' creates convex spline features.

R/spline_monotone.R

@@ -1,4 +1,4 @@
-#' Monotone Splines
+#' Monotone splines
 #'
 #' `step_spline_monotone()` creates a *specification* of a recipe step that
 #' creates monotone spline features.

R/spline_natural.R

@@ -1,4 +1,4 @@
-#' Natural Splines
+#' Natural splines
 #'
 #' `step_spline_natural()` creates a *specification* of a recipe step that
 #' creates natural spline features.

R/spline_nonnegative.R

@@ -1,4 +1,4 @@
-#' Non-Negative Splines
+#' Non-negative splines
 #'
 #' `step_spline_nonnegative()` creates a *specification* of a recipe step that
 #' creates non-negative spline features.

R/sqrt.R

@@ -1,4 +1,4 @@
-#' Square Root Transformation
+#' Square root transformation
 #'
 #' `step_sqrt()` creates a *specification* of a recipe step that will apply
 #' square root transform to the variables.

R/steps_and_checks.R

@@ -1,4 +1,4 @@
-## Overall Wrappers to Make New `step_X` or `check_Y` Objects
+## Overall wrappers to make new `step_X` or `check_Y` objects
 #'
 #' `step` sets the class of the `step` and `check` is for checks.
 #'

R/string2factor.R

@@ -1,4 +1,4 @@
-#' Convert Strings to Factors
+#' Convert strings to factors
 #'
 #' @description
 #' `step_string2factor()` will convert one or more character vectors to factors

R/tidy.R

@@ -1,4 +1,4 @@
-#' Tidy the Result of a Recipe
+#' Tidy the result of a recipe
 #'
 #' `tidy` will return a data frame that contains information
 #'  regarding a recipe or operation within the recipe (when a `tidy`

R/time.R

@@ -1,4 +1,4 @@
-#' Time Feature Generator
+#' Time feature generator
 #'
 #' `step_time()` creates a *specification* of a recipe step that will convert
 #' date-time data into one or more factor or numeric variables.

R/unorder.R

@@ -1,4 +1,4 @@
-#' Convert Ordered Factors to Unordered Factors
+#' Convert ordered factors to unordered factors
 #'
 #' `step_unorder()` creates a *specification* of a recipe step that will turn
 #' ordered factor variables into unordered factor variables.