Summarize the Advantage of FDA-SelectBoost Over Baselines

Computes the per-scenario and per-level gain of a target method over one or more reference methods. This is intended to make the benchmark story explicit when comparing FDA-aware SelectBoost to existing baselines.

Usage

summarise_benchmark_advantage(
  x,
  target = "selectboost",
  reference = c("plain_selectboost", "stability"),
  level = c("feature", "group", "basis"),
  metric = "f1",
  optimize = c("max", "min"),
  select_c0 = c("best", "all")
)

Arguments

x

An fda_benchmark or fda_simulation_study object.

target

Method whose gain should be assessed.

reference

One or more baseline methods.

level

Evaluation level.

metric

Metric used both for best-c0 selection and for the reported gains.

optimize

Should larger or smaller values of metric be preferred?

select_c0

Keep all c0 rows or only the best one per method and replicate.

Value

A data frame.