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tune_resample(): nested cross-validation using tidymodels
tune/dials with leakage-aware outer
splits.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.learner argument in fit_resample().calibration_summary() and plot_calibration()
for probability calibration checks;
confounder_sensitivity() and
plot_confounder_sensitivity() for sensitivity
analysis.simulate_leakage_suite() for generating controlled leakage
scenarios and benchmarking audit sensitivity.audit_report():
renders a self-contained HTML summary of all audit results for sharing
and review.audit_leakage_by_learner() to audit each learner in a
multi-model fit separately.audit_leakage() for supported tasks, complementing the
existing univariate scan.perm_refit = TRUE or "auto") in
audit_leakage() for a more powerful permutation gap test
when refit data are available.fit_resample() for imbalanced classification tasks.plot_fold_balance(),
plot_overlap_checks(),
plot_perm_distribution(),
plot_time_acf().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.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).bioLeak-intro) rewritten with
guided workflow and leaky-vs-correct comparisons.fit_resample() result aggregation when folds fail
during preprocessing.missForest preprocessing dropping rows.glmnet folds receiving non-numeric design
matrices.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).audit_leakage() with
label-permutation gap test, batch/study association tests, univariate
target leakage scan, and near-duplicate detection.impute_guarded(), predict_guard(),
.guard_fit(), .guard_ensure_levels().LeakSplits, LeakFit,
LeakAudit.glm, glmnet,
ranger, xgboost (via
custom_learners).SummarizedExperiment input support.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.
Health stats visible at Monitor.