WVPlots (version 1.3.7)

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

Description

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

Usage

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

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)
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)