roc
From caret v4.75
by Max Kuhn
Compute the points for an ROC curve
Computes sensitivity and specificity for a variety of cutoffs
- Keywords
- manip
Usage
roc(data, class, dataGrid = TRUE, gridLength = 100, positive = levels(class)[1])
Arguments
- data
- a numeric variable to cut along
- class
- a factor with class memberships. There must be only two classes.
- dataGrid
- should the data define the grid of cut-points? If not a sequence of evenly spaced intervals is used.
- gridLength
- number of intervals to use if the data do not define the grid.
- positive
- a character string for the level of the class variable that defines a "positive" event
Value
- A matrix of results with columns "cutoff", "sensitivity" and "specificity"
Note
The first row in the output has a cutoff of NA
, zero specificity and sensitivity of one.
See Also
Examples
set.seed(6)
testData <- data.frame(x = c(rnorm(200), rnorm(200) + 1),
group = factor(rep(letters[1:2], each = 200)))
densityplot(~testData$x, groups = testData$group, auto.key = TRUE)
roc(testData$x, testData$group)
Community examples
Looks like there are no examples yet.