| Title: | Common S3 Generics not Provided by Base R Methods Related to Model Fitting |
| Version: | 0.1.3 |
| Description: | In order to reduce potential package dependencies and conflicts, generics provides a number of commonly used S3 generics. |
| License: | MIT + file LICENSE |
| URL: | https://generics.r-lib.org, https://github.com/r-lib/generics |
| BugReports: | https://github.com/r-lib/generics/issues |
| Depends: | R (≥ 3.2) |
| Imports: | methods |
| Suggests: | covr, pkgload, testthat (≥ 3.0.0), tibble, withr |
| Config/Needs/website: | tidyverse/tidytemplate |
| Config/testthat/edition: | 3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.2.0 |
| NeedsCompilation: | no |
| Packaged: | 2022-07-05 14:52:13 UTC; davis |
| Author: | Hadley Wickham [aut, cre], Max Kuhn [aut], Davis Vaughan [aut], RStudio [cph] |
| Maintainer: | Hadley Wickham <hadley@rstudio.com> |
| Repository: | CRAN |
| Date/Publication: | 2022-07-05 19:40:02 UTC |
generics: common S3 generics
Description
These are generic functions that can be used to minimize package dependencies when multiple packages have the same method.
Details
An attempt was made to use generic class signatures that were
consistent with existing code. For example, dplyr and
lime both have explain() methods that do very different
things but both take x as their main object. Even though x
would be different in those cases, this package provides access
to the S3 generic so that other packages that may want to create
explain() methods for their objects can do so without loading
either of the other packages.
For example, if a new tidy() method is being developed for a
package, this lightweight package can be the required dependency
to have access to the generic method (instead of depending on
broom and installing its dependencies).
Author(s)
Maintainer: Hadley Wickham hadley@rstudio.com
Authors:
Max Kuhn max@rstudio.com
Davis Vaughan davis@rstudio.com
Other contributors:
RStudio [copyright holder]
See Also
Useful links:
Report bugs at https://github.com/r-lib/generics/issues
Accuracy measures for a model
Description
Returns range of summary measures of the forecast accuracy.
Usage
accuracy(object, ...)
Arguments
object |
A model for which forecasts are required. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Augment data with information from an object
Description
Augment data with information from an object
Usage
augment(x, ...)
Arguments
x |
Model object or other R object with information to append to observations. |
... |
Addition arguments to |
Value
A tibble::tibble() with information about data points.
Methods
No methods found in currently loaded packages.
Calculate statistics.
Description
Calculate statistics.
Usage
calculate(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Factor coercion
Description
Coercion functions for creating factors from other existing objects.
Usage
as.factor(x, ...)
as.ordered(x, ...)
Arguments
x |
A vector of data. |
... |
Other arguments passed on to methods. |
Details
These functions override non-generic factor coercion functions provided in base so that packages can provide methods for different data types. The default methods call the base versions.
Value
For as.factor(), a factor. For as.ordered(),
an ordered factor.
Methods
as.factor()
No methods found in currently loaded packages.
as.ordered()
No methods found in currently loaded packages.
Examples
as.factor(letters[1:5])
as.ordered(letters[1:5])
Time difference coercion
Description
Coercion functions for creating difftime objects from other
existing objects.
Usage
as.difftime(tim, ...)
## Default S3 method:
as.difftime(tim, format = "%X", units = "auto", ...)
Arguments
tim |
A vector specifying a time interval. |
... |
Other arguments passed on to methods. |
format |
A single character specifying the format of |
units |
A single character specifying units in which the results are
desired. Required if |
Details
This function overrides the non-generic as.difftime() function
provided in base so that packages can provide methods for different data
types. The default method call the base version.
Value
A difftime object with an attribute indicating the units.
Methods
See the following help topics for more details about individual methods:
generics
coercion-time-difference:default
Examples
as.difftime(1:5, units = "secs")
as.difftime(c("01:55:22", "01:55:25"))
as.difftime("01", format = "%H")
as.difftime("01", format = "%H", units = "secs")
Configure an object
Description
Finalizes or completes an object.
Usage
compile(object, ...)
Arguments
object |
An object. See the individual method for specifics. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Extract components
Description
components can be used to extract elements from an object.
Usage
components(object, ...)
Arguments
object |
A data separable object. |
... |
Other arguments passed to methods |
Details
For example, decomposition methods and some modelling techniques can be used to decompose a dataset into components of interest. This function is used to extract these components in a tidy data format.
Value
A dataset (tibble::tibble() or similar) containing components from
the object.
Methods
No methods found in currently loaded packages.
Model equations
Description
Display the mathematical representation of a fitted model.
Usage
equation(object, ...)
Arguments
object |
A fitted model object. |
... |
Other arguments passed to methods |
Value
Markup output suitable for rendering the equation.
Methods
No methods found in currently loaded packages.
Extracting the estimating functions of a fitted model.
Description
Extracting the estimating functions of a fitted model.
Usage
estfun(x, ...)
Arguments
x |
A fitted model object. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Evaluate an object.
Description
Evaluate an object.
Usage
evaluate(x, ...)
Arguments
x |
An object. See the individual method for specifics. |
... |
other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Explain details of an object
Description
Explain details of an object
Usage
explain(x, ...)
Arguments
x |
An object. See the individual method for specifics. |
... |
other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Create an interactive visualization appropriate to a particular object type
Description
explore() invokes a function that starts an interactive, pre-defined widget
(e.g. plotly visualization, shiny app, etc.) to investigate the results.
Usage
explore(x, ...)
Arguments
x |
A object |
... |
Other arguments passed to methods |
Value
NULL (invisibly) or some other data type (e.g. tibble) depending on
the application.
Methods
No methods found in currently loaded packages.
Estimate model parameters.
Description
Estimates parameters for a given model from a set of data.
Usage
fit(object, ...)
Arguments
object |
An object. See the individual method for specifics. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Estimate model parameters.
Description
Estimates parameters for a given model from a set of data in the form of
a set of predictors (x) and outcome(s) (y).
Usage
fit_xy(object, ...)
Arguments
object |
An object. See the individual method for specifics. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Forecasting from an object
Description
The functions allow producing forecasts based on the provided object.
Usage
forecast(object, ...)
Arguments
object |
A model for which forecasts are required. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Generate values based on inputs
Description
Generate values based on inputs
Usage
generate(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Glance at an object
Description
Construct a single row summary "glance" of a model, fit, or other object
Usage
glance(x, ...)
Arguments
x |
model or other R object to convert to single-row data frame |
... |
other arguments passed to methods |
Details
glance methods always return either a one-row data frame (except on
NULL, which returns an empty data frame)
Methods
No methods found in currently loaded packages.
Construct hypotheses.
Description
Construct hypotheses.
Usage
hypothesize(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Interpolate missing values
Description
Interpolates missing values provided in the training dataset using the fitted model.
Usage
interpolate(object, ...)
Arguments
object |
A fitted model object |
... |
Other arguments passed to methods |
Value
A dataset (tibble::tibble() or similar) of the same structure as
the input dataset with missing values from the response variable replaced
with interpolated values.
Methods
No methods found in currently loaded packages.
Estimate model parameters.
Description
Estimates parameters for a given model from a set of data.
Usage
learn(x, ...)
Arguments
x |
An object. See the individual method for specifics. |
... |
other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Determine the minimum set of model fits
Description
min_grid() determines exactly what models should be fit in order to
evaluate the entire set of tuning parameter combinations. This is for
internal use only and the API may change in the near future.
Usage
min_grid(x, grid, ...)
Arguments
x |
A model specification. |
grid |
A tibble with tuning parameter combinations. |
... |
Not currently used. |
Value
A tibble with the minimum tuning parameters to fit and an additional list column with the parameter combinations used for prediction.
Methods
No methods found in currently loaded packages.
Prune or reduce an object
Description
Prune or reduce an object
Usage
prune(tree, ...)
Arguments
tree |
A fitted model object. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Compute relative rankings of a collection of objects
Description
rank_results() computes relative ranks of a collection of objects and
returns a summary of the results.
Usage
rank_results(x, ...)
Arguments
x |
A collection of objects |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Refitting models
Description
Refitting models
Usage
refit(object, ...)
Arguments
object |
A fitted model object. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Determine packages required by objects
Description
Determine packages required by objects
Usage
required_pkgs(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods |
Value
A character string of packages that are required.
Methods
No methods found in currently loaded packages.
Set operations
Description
Union (union()), intersect (intersect()), difference (setdiff()),
and equality (setequal()) for two vectors representing sets. Determine
membership with is.element().
Usage
intersect(x, y, ...)
union(x, y, ...)
setdiff(x, y, ...)
setequal(x, y, ...)
is.element(el, set, ...)
Arguments
x, y |
Vectors to combine. |
... |
Other arguments passed on to methods. |
el, set |
Element and set to compare. |
Details
These functions override the set functions provided in base to make them generic so that packages can provide methods for different data types. The default methods call the base versions.
Value
For union(), intersect(), and setdiff(), a vector with all
duplicate removed.
For setequal() and is.element(), a logical TRUE or FALSE.'
Methods
intersect()
No methods found in currently loaded packages.
union()
No methods found in currently loaded packages.
setdiff()
No methods found in currently loaded packages.
setequal()
No methods found in currently loaded packages.
is.element()
No methods found in currently loaded packages.
Examples
intersect(1:5, 4:8)
union(1:5, 4:8)
setdiff(1:5, 4:8)
setdiff(4:8, 1:5)
Specify variables or other quantities.
Description
Specify variables or other quantities.
Usage
specify(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Turn an object into a tidy tibble
Description
Turn an object into a tidy tibble
Usage
tidy(x, ...)
Arguments
x |
An object to be converted into a tidy |
... |
Additional arguments to tidying method. |
Value
A tibble::tibble() with information about model components.
Methods
No methods found in currently loaded packages.
Estimate model parameters.
Description
Estimates parameters for a given model from a set of data.
Usage
train(x, ...)
Arguments
x |
An object. See the individual method for specifics. |
... |
other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Declare tunable parameters
Description
Returns information on potential hyper-parameters that can be optimized.
Usage
tunable(x, ...)
Arguments
x |
An object, such as a recipe, recipe step, workflow, or model specification. |
... |
Other arguments passed to methods |
Details
For a model specification, an engine must be chosen.
If the object has no tunable parameters, a tibble with no rows is returned.
The information about the default parameter object takes the form of a
named list with an element for the function call and an optional element for
the source of the function (e.g. the dials package). For model
specifications, If the parameter is unknown to the underlying tunable
method, a NULL is returned.
Value
A tibble with a column for the parameter name, information on the
default method for generating a corresponding parameter object, the
source of the parameter (e.g. "recipe", etc.), and the component within
the source. For the component column, a little more specificity is given
about the location of the parameter (e.g. "step_normalize" for recipes or
"boost_tree" for models). The component_id column contains the unique step
id field or, for models, a logical for whether the model specification
argument was a main parameter or one associated with the engine.
Methods
No methods found in currently loaded packages.
Determine arguments tagged for tuning
Description
tune_args() takes an object such as a model specification or a recipe and
returns a tibble of information on all possible tunable arguments and
whether or not they are actually tunable.
Usage
tune_args(object, ...)
Arguments
object |
A |
... |
Other arguments passed to methods. |
Details
The source column is determined differently for a
model_spec or a recipe (with additional detail on the type).
The id field has any identifier that was passed from tune::tune() (e.g.
tune("some note")). If no additional detail was used in that function,
the id field reverts to the name of the parameters.
Value
A tibble with columns for the parameter name (name), whether it
contains any tunable value (tune), the id for the parameter (id),
and the information on where the parameter was located (source).
Methods
No methods found in currently loaded packages.
Calculation of variable importance
Description
A generic method for calculating variable importance for model objects.
Usage
var_imp(object, ...)
Arguments
object |
A fitted model object. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Find any arguments that are not fully specified.
Description
Find any arguments that are not fully specified.
Usage
varying_args(object, ...)
Arguments
object |
An object. See the individual method for specifics. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.
Visualize a data set or object.
Description
Visualize a data set or object.
Usage
visualize(x, ...)
Arguments
x |
A data frame or other object. |
... |
Other arguments passed to methods |
Methods
No methods found in currently loaded packages.