Visualize cue accuracies (as points in ROC space)

showcues plots the cue accuracies of an FFTrees object created by the FFTrees function (as points in ROC space).

If the optional arguments cue.accuracies and alt.goal are specified, their values take precedence over the corresponding settings of an FFTrees object x (but do not change x).

showcues is called when the main plot.FFTrees function is set to what = "cues".

showcues(
  x = NULL,
  cue.accuracies = NULL,
  alt.goal = NULL,
  main = NULL,
  top = 5,
  quiet = list(ini = TRUE, fin = FALSE, set = TRUE),
  ...
)

Arguments

x

An FFTrees object created by the FFTrees function.

cue.accuracies

An optional data frame specifying cue accuracies directly (without specifying FFTrees object x).

alt.goal

An optional alternative goal to sort the current cue accuracies (without using the goal of FFTrees object x).

main

A main plot title (as character string).

top

How many of the top cues should be highlighted (as an integer)?

quiet

Should user feedback messages be suppressed (as a list of 3 logical arguments)? Default: quiet = list(ini = TRUE, fin = FALSE, set = FALSE).

...

Graphical parameters (passed to plot).

Value

A plot showing cue accuracies (of an FFTrees object) (as points in ROC space).

See also

print.FFTrees for printing FFTs; plot.FFTrees for plotting FFTs; summary.FFTrees for summarizing FFTs; FFTrees for creating FFTs from and applying them to data.

Other plot functions: plot.FFTrees()

Examples

# Create fast-and-frugal trees (FFTs) for heart disease:
heart.fft <- FFTrees(formula = diagnosis ~ .,
                     data = heart.train,
                     data.test = heart.test,
                     main = "Heart Disease",
                     decision.labels = c("Healthy", "Diseased")
                     )
#> ✔ Created an FFTrees object.
#>   Ranking 13 cues:  ■■■■■■■■                          23% | ETA:  1s
#>   Ranking 13 cues:  ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■  100% | ETA:  0s
#> 
#> ✔ Ranked 13 cues (optimizing 'bacc').
#> ✔ Created 7 FFTs with 'ifan' algorithm (chasing 'bacc').
#> ✔ Defined 7 FFTs.
#> ✔ Applied 7 FFTs to 'train' data.
#> ✔ Ranked 7 FFTs by 'train' data.
#> ✔ Applied 7 FFTs to 'test' data.
#> ✔ Expressed 7 FFTs in words.

# Show cue accuracies (in ROC space):
showcues(heart.fft,
         main = "Predicting heart disease")
#> Plotting cue training statistics:
#> — Cue accuracies ranked by bacc
#>