Plot the cumulative gain curve of a sort-order with extra notation

Plot the cumulative gain curve of a sort-order with extra notation.

GainCurvePlotWithNotation(
  frame,
  xvar,
  truthVar,
  title,
  gainx,
  labelfun,
  ...,
  sort_by_model = TRUE,
  estimate_sig = FALSE,
  large_count = 1000,
  model_color = "darkblue",
  wizard_color = "darkgreen",
  shadow_color = "darkgray",
  crosshair_color = "red",
  text_color = "black"
)

Arguments

frame	data frame to get values from
xvar	name of the independent (input or model score) column in frame
truthVar	name of the dependent (output or result to be modeled) column in frame
title	title to place on plot
gainx	the point on the x axis corresponding to the desired label
labelfun	a function to return a label for the marked point
...	no unnamed argument, added to force named binding of later arguments.
sort_by_model	logical, if TRUE use the model to calculate gainy, else use wizard.
estimate_sig	logical, if TRUE compute significance
large_count	numeric, upper bound target for number of plotting points
model_color	color for the model curve
wizard_color	color for the "wizard" (best possible) curve
shadow_color	color for the shaded area under the curve
crosshair_color	color for the annotation location lines
text_color	color for the annotation text

Details

This is the standard gain curve plot (see GainCurvePlot) with a label attached to a particular value of x. The label is created by a function labelfun, which takes as inputs the x and y coordinates of a label and returns a string (the label).

By default, uses the model to calculate the y value of the calculated point; to use the wizard curve, set sort_by_model = FALSE

See also

GainCurvePlot

Examples

set.seed(34903490)
y = abs(rnorm(20)) + 0.1
x = abs(y + 0.5*rnorm(20))
frm = data.frame(model=x, value=y)
gainx = 0.25  # get the predicted top 25% most valuable points as sorted by the model
# make a function to calculate the label for the annotated point
labelfun = function(gx, gy) {
  pctx = gx*100
  pcty = gy*100

  paste("The predicted top ", pctx, "% most valuable points by the model\n",
        "are ", pcty, "% of total actual value", sep='')
}
WVPlots::GainCurvePlotWithNotation(frm, "model", "value",
   title="Example Gain Curve with annotation",
   gainx=gainx,labelfun=labelfun)

# now get the top 25% actual most valuable points

labelfun = function(gx, gy) {
  pctx = gx*100
  pcty = gy*100

  paste("The actual top ", pctx, "% most valuable points\n",
        "are ", pcty, "% of total actual value", sep='')
}

WVPlots::GainCurvePlotWithNotation(frm, "model", "value",
   title="Example Gain Curve with annotation",
   gainx=gainx,labelfun=labelfun, sort_by_model=FALSE)