LiftCurvePlotList {WVPlots}

Plot the cumulative lift curves of a sort-order.

Description

Plot the cumulative lift curves of a sort-order.

Usage

LiftCurvePlotList(
  frame,
  xvars,
  truthVar,
  title,
  ...,
  truth_target = NULL,
  palette = "Dark2"
)

LiftCurveListPlot(
  frame,
  xvars,
  truthVar,
  title,
  ...,
  truth_target = NULL,
  palette = "Dark2"
)

Arguments

frame

data frame to get values from

xvars

name of the independent (input or model score) columns in frame

truthVar

name of the dependent (output or result to be modeled) column in frame

title

title to place on plot

...

no unnamed argument, added to force named binding of later arguments.

truth_target

if not NULL compare to this scalar value.

palette

color palette for the model curves

Details

The use case for this visualization is to compare a predictive model score to an actual outcome (either binary (0/1) or continuous). In this case the lift curve plot measures how well the model score sorts the data compared to the true outcome value.

The x-axis represents the fraction of items seen when sorted by score, and the y-axis represents the lift seen so far (cumulative value of model over cummulative value of random selection)..

Examples

if (requireNamespace('data.table', quietly = TRUE)) {
	# don't multi-thread during CRAN checks
		data.table::setDTthreads(1)
}

set.seed(34903490)
y = abs(rnorm(20)) + 0.1
x = abs(y + 0.5*rnorm(20))
frm = data.frame(model=x, value=y)
WVPlots::LiftCurvePlotList(frm, c("model", "value"), "value",
   title="Example Continuous Lift Curves")