Skip to content

tune 2.1.0

Latest
Latest

Choose a tag to compare

View all tags
@topepo topepo released this 17 Apr 16:44
v2.1.0
4c74638
This commit was created on GitHub.com and signed with GitHub’s verified signature.
GPG key ID: B5690EEEBB952194
Verified
Learn about vigilant mode.

  • Model tuning has been enabled for quantile regression models. (#1125)

  • When calculating resampling estimates, we can now use a weighted mean based on the number of rows in the assessment set. You can opt-in to this using the new add_resample_weights() function. See ?calculate_resample_weights (#990)

  • The warning threshold when check the size of a workflow is now a parameter to the control functions and has a new default of 100MB. (#914)

  • Tuning of models with submodel parameters now predicts all submodels at once (again) to speed up the tuning process (#1140).

  • tune_bayes() now uses an uncertainty sample if all predictions from the Gaussian process model fail (#1167).

Breaking Changes

  • The Gaussian process model package was changed from \pkg{GPfit} to \pkg{GauPro} because the former is no longer actively maintained. There are some differences:

    • Fit diagnostics are computed and reported. If the fit quality is poor, an "uncertainty sample" that is furthest away from the existing data is used as the new candidate.
    • The GP no longer uses binary indicators for qualitative predictors. Instead, a "categorical kernel" is used for those parameter columns. Fewer starting values are required with this change.
    • For numeric predictors, the Matern 3/2 kernel is always used.

Bug Fixes

  • Fixed a bug where models with submodel parameters would train all calibration models on predictions from a single submodel value instead of the correct value for each submodel (#1144).

  • A bug was fixed where NULL results generated during simulated annealing would cause errors when logging.

  • Fixed a bug for cases where we tune a grid without a model parameter but with a postprocessing parameter (#1119)

  • Fixed a bug in augment() when using last_fit() objects (#1110)

  • In tune_grid(), a bug was fixed that caused inefficiency where preprocessing steps were applied to data being predicted several times (redundantly). We now execute that operation once. (#1101)

Other Changes

  • The developer functions val_class_and_single() and val_class_or_null() are now deprecated (#1161).

  • check_metrics() is deprecated in favor of check_metrics_arg() (#1160).

  • finalize_workflow_preprocessor() is deprecated (#1157).

  • Prepends a period to the name, and exports the following functions. This is to improve integration with other packages:

    • check_grid() (e.g., now named .check_grid())
    • determine_pred_types()
    • get_config_key()
    • loop_over_all_stages()
    • update_parallel_over()
    • get_data_subsets()
Assets 2
Loading