Plot the cumulative lift curves of a sort-order.

Plot the cumulative lift curves of a sort-order.

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

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")