These functions calculate the fp() (number of false positives) of a measurement system compared to the reference results (the "truth").

## Usage

fp(data, ...)

# S3 method for data.frame
fp(
data,
truth,
estimate,
estimator = NULL,
na_rm = FALSE,
event_level = "first",
...
)

fp_vec(
truth,
estimate,
estimator = NULL,
na_rm = FALSE,
event_level = "first",
...
)

## Arguments

data

Either a data.frame containing the truth and estimate columns, or a table/matrix where the true class results should be in the columns of the table.

...

Not currently used.

truth

The column identifier for the true class results (that is a factor). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For _vec() functions, a factor vector.

estimate

The column identifier for the predicted class results (that is also factor). As with truth this can be specified different ways but the primary method is to use an unquoted variable name. For _vec() functions, a factor vector.

estimator

One of: "binary", "macro", "macro_weighted", or "micro" to specify the type of averaging to be done. "binary" is only relevant for the two class case. The other three are general methods for calculating multiclass metrics. The default will automatically choose "binary" or "macro" based on estimate.

na_rm

A logical value indicating whether NA values should be stripped before the computation proceeds.

event_level

A single string. Either "first" or "second" to specify which level of truth to consider as the "event". This argument is only applicable when estimator = "binary". The default uses an internal helper that generally defaults to "first", however, if the deprecated global option yardstick.event_first is set, that will be used instead with a warning.

## Value

A tibble with columns .metric, .estimator, and .estimate with 1 row of values. For grouped data frames, the number of rows returned will be the same as the number of groups. For fp_vec(), a single numeric value (or NA).