modeltime.ensemble 1.1.0

modeltime.ensemble 1.1.0

• Major update to align with tune 2.0.0.

  • Updated internal logic for compatibility with the new column naming conventions in resampling results (.model_desc vs .row).
  • Improved handling of .resample_id and .row_id to ensure keys remain unique across resamples.
  • Adjusted recipe preparation to exclude .resample_id consistently.
  • Refined model tuning vs non-tuning workflows for clarity and stability.
  • Enhanced error reporting and verbose output for improved user feedback.

• Dependency updates:

  • tune (>= 2.0.0)
  • modeltime.resample (>= 0.3.0)

• Version bump to 1.1.0 for CRAN submission.

Full Changelog: v1.0.5...v1.1.0

modeltime.ensemble 1.0.5

What's Changed

• refit submodels before fitting resamples by @regisely in #19
• Remove tidyverse dep by @olivroy in #24
• Update R-CMD-check.yaml by @olivroy in #25
• Update R-CMD-check.yaml by @olivroy in #26
• Delete docs directory by @olivroy in #27
• Update for the next version of tune by @hfrick in #32

New Contributors

• @regisely made their first contribution in #19
• @olivroy made their first contribution in #24
• @hfrick made their first contribution in #32

Full Changelog: V0.4.2...v1.0.5

modeltime.ensemble 0.4.2

Compatibility with modeltime 0.7.0.

• Calibration: Added "id" feature to enable accuracy and confidence intervals by time series ID.

Improvements (included in modeltime.ensemble 0.4.1)

• Improvements for parallel processing during refitting (available in modeltime 0.6.0).
• Requires modeltime 0.6.0 and parsnip 0.1.6 to align with xgboost upgrades.

Modeltime Ensemble 0.4.0

Recursive Ensembles

• recursive() - The recursive() function is extended to recursive ensembles for both single time series and multiple time series models (panel data).
• "Forecasting with Recursive Ensembles" - A new forecasting vignette for using recurive() with ensembles.

Fixes

• modeltime_forecast() now returns NA when missing values are present in the sub-model predictions.