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modeltime.ensemble (development version)

modeltime.ensemble 1.0.4

  • #31 Fixes issue with metric argument not being specified:
Error in `tune::show_best()`:
! `...` must be empty.
✖ Problematic argument:
• ..1 = metric
ℹ Did you forget to name an argument?

modeltime.ensemble 1.0.3

CRAN release: 2023-04-18

  • Resubmit to CRAN (following timetk archival)

modeltime.ensemble 1.0.2

CRAN release: 2022-10-18

  • Update tests for workflows mode = “regression”

modeltime.ensemble 1.0.1

CRAN release: 2022-06-09

Fixes

  • Updates for hardhat 1.0.0

modeltime.ensemble 1.0.0

CRAN release: 2021-10-19

NEW Nested Modeltime Ensembles

In modeltime 1.0.0, we introduced Nested Forecasting as a way to forecast many time series iteratively. In modeltime.ensemble 1.0.0, we introduce nested ensembles that can improve forecasting performance and be applied to many time series iteratively. We have added:

New Vignette (Nested Ensembles)

modeltime.ensemble 0.4.2

CRAN release: 2021-07-16

Compatibility with modeltime 0.7.0.

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

modeltime.ensemble 0.4.1

CRAN release: 2021-05-31

  • 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

CRAN release: 2021-04-05

Recursive Ensembles

Fixes

modeltime.ensemble 0.3.0

CRAN release: 2020-11-06

Panel Data

Changes

modeltime.ensemble 0.2.0

CRAN release: 2020-10-09

Stacked Ensembles (Breaking Changes)

The process for creating stacked ensembles is split into 2 steps:

Note - modeltime_refit(stacked_ensemble) is still one step, which is the best way to handle refitting since multiple stacked models may have different submodel compositions. An additional argument, resamples can be provided to train stacked ensembles made with ensemble_model_spec().

modeltime.ensemble 0.1.0

CRAN release: 2020-10-07

  • Initial release of modeltime.ensemble.