modeltime.resample 0.3.0
CRAN release: 2025-09-03
🚀 New Features & Improvements
-
Compatibility with tune 2.0.0
- Updated internals to support new
tune::fit_resamples()
behavior. - Improved handling of
.predictions
column reconstruction when missing. - Added robust fallback logic to normalize truth/prediction columns across versions.
- Updated internals to support new
-
Improved Resampling Functions
-
modeltime_fit_resamples()
now ensures predictions are always saved. - Added deterministic seeding (
withr::with_seed()
) for reproducible resample fits. - Better error handling: failed resample fits now produce
.notes
with clear error messages.
-
-
Plotting Enhancements
-
plot_modeltime_resamples()
now standardizes truth/estimate detection. - Improved facetting and summary-line consistency.
- More graceful error messages if truth/pred columns cannot be identified.
- Optional interactive output improved with Plotly checks.
-
-
Utility Upgrades
-
unnest_modeltime_resamples()
more robust:- Ensures
.predictions
column exists (reconstructed if missing). - Clear actionable errors when predictions are unavailable.
- Guarantees
.row_id
assignment for comparing models across resamples.
- Ensures
-
🛠 Dependency Updates
-
tune (>= 2.0.0)
is now required. - Added
withr
toImports
. - Retained compatibility with older
tune
versions (<2.0.0) via conditional handling.
⚡ Internal Improvements
- Standardized use of
rlang::abort(message=...)
for consistent error messages. - Reduced reliance on
tictoc
/progressr
in favor of clearer progress reporting. - Expanded
utils::globalVariables()
for safer NSE handling acrossdplyr
/tidyr
.
modeltime.resample 0.2.0
CRAN release: 2021-03-14
-
modeltime_resample_accuracy()
(#1): When user specifiessummary_fns = NULL
, returns unsummarized resample metrics with “.resample_id”