bioLeak 0.2.0
New features
- Leak-safe hyperparameter tuning via
tune_resample(): nested cross-validation using tidymodels
tune/dials with leakage-aware outer
splits.
- Tidymodels interoperability:
fit_resample() now accepts rsample rset/rsplit
objects as splits, recipes::recipe for
preprocessing, workflows::workflow as learner,
and yardstick::metric_set for metrics.
as_rsample() converts LeakSplits to an
rsample rset.
- Parsnip model specs accepted directly as the
learner argument in fit_resample().
- Diagnostics polish: new
calibration_summary() and plot_calibration()
for probability calibration checks;
confounder_sensitivity() and
plot_confounder_sensitivity() for sensitivity
analysis.
- Simulation utility
simulate_leakage_suite() for generating controlled leakage
scenarios and benchmarking audit sensitivity.
- HTML audit report via
audit_report():
renders a self-contained HTML summary of all audit results for sharing
and review.
- Multi-learner auditing with
audit_leakage_by_learner() to audit each learner in a
multi-model fit separately.
- Multivariate target leakage scan enabled by default
in
audit_leakage() for supported tasks, complementing the
existing univariate scan.
- Refit-based permutations
(
perm_refit = TRUE or "auto") in
audit_leakage() for a more powerful permutation gap test
when refit data are available.
- Class weights support in
fit_resample() for imbalanced classification tasks.
- New plotting functions:
plot_fold_balance(),
plot_overlap_checks(),
plot_perm_distribution(),
plot_time_acf().
Improvements
- S4 classes (
LeakSplits, LeakFit,
LeakAudit) now include setValidity checks for
slot consistency.
summary() methods for LeakFit,
LeakAudit, and LeakTune improved with clearer
console output and edge-case handling.impute_guarded() gains enhanced diagnostics and RNG
safety..guard_fit() and .guard_ensure_levels()
made more robust with better error messages.- Permutation label factory (
permute_labels) gains
verbose mode, digest-based caching, and improved stratification
safety.
audit_leakage() handles NA metrics gracefully and
enriches trail metadata.make_split_plan() improved stratification logic and
reproducible seeding.audit_report() now renders from a temporary copy of the
Rmd template to avoid write failures on read-only file systems
(e.g. during R CMD check).- Comprehensive vignette (
bioLeak-intro) rewritten with
guided workflow and leaky-vs-correct comparisons.
Bug fixes
- Fixed
fit_resample() result aggregation when folds fail
during preprocessing.
- Fixed
missForest preprocessing dropping rows.
- Fixed single-level factors causing errors in guarded
preprocessing.
- Fixed filter keep-column alignment by name.
- Fixed
glmnet folds receiving non-numeric design
matrices.
- Fixed constant imputation for categorical data.
- Fixed RANN self-neighbour filter in duplicate detection.
- Fixed various edge cases in outcome extraction and hashing
utilities.
- Resolved multiple CRAN check issues (Rd formatting, example runtime,
read-only file-system writes).
bioLeak 0.1.0
- Initial release.
- Core pipeline:
make_split_plan() for
leakage-aware splitting (subject-grouped, batch-blocked, study
leave-out, time-ordered); fit_resample() for
cross-validated fitting with built-in guarded preprocessing (train-only
imputation, normalisation, filtering, feature selection).
- Leakage auditing:
audit_leakage() with
label-permutation gap test, batch/study association tests, univariate
target leakage scan, and near-duplicate detection.
- Guarded preprocessing helpers:
impute_guarded(), predict_guard(),
.guard_fit(), .guard_ensure_levels().
- S4 class system:
LeakSplits, LeakFit,
LeakAudit.
- Support for binomial, multiclass, regression, and survival
tasks.
- Built-in learners:
glm, glmnet,
ranger, xgboost (via
custom_learners).
SummarizedExperiment input support.- Vignette and comprehensive documentation.