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Calculate area under ROC curve

auc.Rd

Calculates area under curve (AUC) of a predictor's ROC curve.

Usage

auc(data = NULL, response, predictor, .condition = NULL)

Arguments

data

A data.frame or extension (e.g. a tibble) containing values for predictors and response variables.

response

A data variable which must be a factor, integer or character vector representing the prediction outcome on each observation (Gold Standard).

If the variable presents more than two possible outcomes, classes or categories:

  • The outcome of interest (the one to be predicted) will remain distinct.

  • All other categories will be combined into a single category.

New combined category represents the "absence" of the condition to predict. See .condition for more information.

predictor

A data variable which must be numeric, representing values of a classifier or predictor for each observation.

.condition

A value from response that represents class, category or condition of interest which wants to be predicted.

If NULL, condition of interest will be selected automatically depending on response type.

Once the class of interest is selected, rest of them will be collapsed in a common category, representing the "absence" of the condition to be predicted.

See vignette("selecting-condition") for further information on how automatic selection is performed and details on selecting the condition of interest.

Value

A numerical value representing the area under ROC curve.

Examples

# Calc AUC of Sepal.Width as a classifier of setosa species
auc(iris, Species, Sepal.Width)
#> [1] 0.8796
# Change class to predict to virginica
auc(iris, Species, Sepal.Width, .condition = "virginica")
#> [1] 0.4146