# panel.lift2

From caret v6.0-37
by Max Kuhn

##### Lattice Panel Functions for Lift Plots

Two panel functions that be used in conjunction with `lift`

.

- Keywords
- hplot

##### Usage

`panel.lift(x, y, ...)`panel.lift2(x, y, pct = 0, values = NULL, ...)

##### Arguments

- 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
- ...
- options to pass to
`panel.xyplot`

##### Details

`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).

##### See Also

##### Examples

```
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)
```

*Documentation reproduced from package caret, version 6.0-37, License: GPL-2*

### Community examples

Looks like there are no examples yet.