Description Usage Arguments Details Author(s) See Also Examples
Two panel functions that be used in conjunction with lift
.
1 2 3 | panel.lift(x, y, ...)
panel.lift2(x, y, pct = 0, values = NULL, ...)
|
x |
the percentage of searched to be plotted in the scatterplot |
y |
the percentage of events found to be plotted in the scatterplot |
pct |
the baseline percentage of true events in the data |
values |
A vector of numbers between 0 and 100 specifying reference values for the percentage of samples found (i.e. the y-axis). Corresponding points on the x-axis are found via interpolation and line segments are shown to indicate how many samples must be tested before these percentages are found. The lines use either the |
... |
options to pass to |
panel.lift
plots the data with a simple (black) 45 degree reference line.
panel.lift2
is the default for lift
and plots the
data points with a shaded region encompassing the space between to the random model and perfect model trajectories. The color of the region is determined by the lattice reference.line
information (see example below).
Max Kuhn
lift
, panel.xyplot
, xyplot
, trellis.par.set
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | set.seed(1)
simulated <- data.frame(obs = factor(rep(letters[1:2], each = 100)),
perfect = sort(runif(200), decreasing = TRUE),
random = runif(200))
regionInfo <- trellis.par.get("reference.line")
regionInfo$col <- "lightblue"
trellis.par.set("reference.line", regionInfo)
lift2 <- lift(obs ~ random + perfect, data = simulated)
lift2
xyplot(lift2, auto.key = list(columns = 2))
## use a different panel function
xyplot(lift2, panel = panel.lift)
|
Loading required package: lattice
Loading required package: ggplot2
Call:
lift.formula(x = obs ~ random + perfect, data = simulated)
Models: random, perfect
Event: a (50%)
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