Compute area under precision-recall curve

Compute the area under the precision-recall curve given pr curve data. This function is mainly intended for generating plot data. For computation of the area under the curve, use compute_pr_auc. The function uses a simple trapezoidal rule approximation along the steps of the generated curve data.

compute_pr_auc_from_curve(
  pr_curve_data,
  grouping_vars = NULL,
  drop_empty_groups = options::opt("drop_empty_groups")
)

Arguments

pr_curve_data

A data.frame as produced by compute_pr_curve, containing columns "searchspace_id", "prec", "rec", "prec_cummax", "mode".

grouping_vars

Additional columns of the input data to group by.

drop_empty_groups

Should empty levels of factor variables be dropped in grouped set retrieval computation? (Defaults to TRUE, overwritable using option 'casimir.drop_empty_groups' or environment variable 'R_CASIMIR_DROP_EMPTY_GROUPS')

Value

A data.frame with a column "pr_auc" and optional grouping_vars.

See also

compute_pr_curve

Examples

library(ggplot2)
library(casimir)

gold <- tibble::tribble(
  ~doc_id, ~label_id,
  "A", "a",
  "A", "b",
  "A", "c",
  "B", "a",
  "B", "d",
  "C", "a",
  "C", "b",
  "C", "d",
  "C", "f"
)

pred <- tibble::tribble(
  ~doc_id, ~label_id, ~score, ~rank,
  "A", "a", 0.9, 1,
  "A", "d", 0.7, 2,
  "A", "f", 0.3, 3,
  "A", "c", 0.1, 4,
  "B", "a", 0.8, 1,
  "B", "e", 0.6, 2,
  "B", "d", 0.1, 3,
  "C", "f", 0.1, 3,
  "C", "c", 0.2, 1,
  "C", "e", 0.2, 1
)

pr_curve <- compute_pr_curve(
  gold,
  pred,
  mode = "doc-avg",
  optimize_cutoff = TRUE
)

auc <- compute_pr_auc_from_curve(pr_curve)

# note that pr curves take the cummax(prec), not the precision
ggplot(pr_curve$plot_data, aes(x = rec, y = prec_cummax)) +
  geom_point(
    data = pr_curve$opt_cutoff,
    aes(x = rec, y = prec_cummax),
    color = "red",
    shape = "star"
  ) +
  geom_text(
    data = pr_curve$opt_cutoff,
    aes(
      x = rec + 0.2, y = prec_cummax,
      label = paste("f1_opt =", round(f1_max, 3))
    ),
    color = "red"
  ) +
  geom_path() +
  coord_cartesian(xlim = c(0, 1), ylim = c(0, 1))