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inst/benchmarks/run-benchmark.R reproduces a benchmark
of fastgbm against gbm, xgboost,
and ranger on six real survival datasets from the
biostatlab package (pbc,
heart_failure, breast,
colon_cancer, crc_mondaca2020,
framingham), under an equal-hyperparameter-grid regime with
repeated 70/30 train/test splits.
This writes, under inst/benchmarks/:
benchmark-results.csv – one row per (dataset, model,
repeat), with training time, prediction time, and Harrell’s
C-index;benchmark-summary.csv – median/IQR per (dataset,
model), plus paired win/loss/tie counts of fastgbm against
each competitor;parallel-speedup.csv – threads = 1
vs. threads = <hardware concurrency> training time on
the largest dataset (framingham);session-info.txt – R/package versions, OS, seed, and
hyperparameters, for reproducibility.The full write-up, with tables and figures generated directly from
these CSVs, is in paper/fastgbm-benchmark.qmd (renders to
fastgbm-benchmark.pdf via quarto render).
Results are reported honestly (win/loss/tie per dataset), not as a
universal superiority claim – see the paper’s Comparative Summary
section.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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