metric_vec_template() is useful alongside metric_summarizer() for
implementing new custom metrics. metric_summarizer() calls the metric
function inside dplyr::summarise(). metric_vec_template() is a
generalized function that calls the core implementation of a metric function,
and includes a number of checks on the types, lengths, and argument inputs.
metric_vec_template(
metric_impl,
truth,
estimate,
na_rm = TRUE,
cls = "numeric",
estimator = NULL,
case_weights = NULL,
...
)The core implementation function of your custom metric. This core implementation function is generally defined inside the vector method of your metric function.
The realized vector of truth. This is either a factor
or a numeric.
The realized estimate result. This is either a numeric
vector, a factor vector, or a numeric matrix (in the case of multiple
class probability columns) depending on your metric function.
A logical value indicating whether NA values should be
stripped before the computation proceeds. NA values are removed
before getting to your core implementation function so you do not have to
worry about handling them yourself. If na_rm=FALSE and any NA values
exist, then NA is automatically returned.
A character vector of length 1 or 2 corresponding to the
class that truth and estimate should be, respectively. If truth and
estimate are of the same class, just supply a vector of length 1. If
they are different, supply a vector of length 2. For matrices, it is best
to supply "numeric" as the class to check here.
The type of averaging to use. By this point, the averaging
type should be finalized, so this should be a character vector of length 1\.
By default, this character value is required to be one of: "binary",
"macro", "micro", or "macro_weighted". If your metric allows more
or less averaging methods, override this with averaging_override.
Optionally, the realized case weights, as a numeric
vector. This must be the same length as truth, and will be considered in
the na_rm checks. If supplied, this will be passed on to metric_impl as
the named argument case_weights.
Extra arguments to your core metric function, metric_impl, can
technically be passed here, but generally the extra args are added through
R's scoping rules because the core metric function is created on the fly
when the vector method is called.
metric_vec_template() is called from the vector implementation of your
metric. Also defined inside your vector implementation is a separate
function performing the core implementation of the metric function. This
core function is passed along to metric_vec_template() as metric_impl.
metric_summarizer() finalize_estimator() dots_to_estimate()