modeltime.resample 0.3.0
🚀 New Features & Improvements
-
Compatibility with tune 2.0.0
- Updated internals to support new
tune::fit_resamples()behavior. - Improved handling of
.predictionscolumn 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
.noteswith 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
.predictionscolumn exists (reconstructed if missing). - Clear actionable errors when predictions are unavailable.
- Guarantees
.row_idassignment for comparing models across resamples.
- Ensures
-
🛠 Dependency Updates
tune (>= 2.0.0)is now required.- Added
withrtoImports. - Retained compatibility with older
tuneversions (<2.0.0) via conditional handling.
⚡ Internal Improvements
- Standardized use of
rlang::abort(message=...)for consistent error messages. - Reduced reliance on
tictoc/progressrin favor of clearer progress reporting. - Expanded
utils::globalVariables()for safer NSE handling acrossdplyr/tidyr.
📦 CRAN Prep
- Bumped version to 0.3.0 for CRAN release.
- NEWS and DESCRIPTION updated.
Full Changelog: v0.2.4...v0.3.0