evaluate(), when used on a grouped data frame. The row order in the output was not guaranteed to fit the grouping keys.Fixes documentation in cross_validate_fn(). The examples section contained an unreasonable number of mistakes :-)
In cross_validate_fn(), warnings and messages from the predict function are now included in Warnings and Messages. The warnings are counted in Other Warnings.
Breaking change: In evaluate(), when type is multinomial, the output is now a single tibble. The Class Level Results are included as a nested tibble.
Breaking change: In baseline(), lmer models are now fitted with REML = FALSE by default.
Adds REML argument to baseline().
cross_validate_fn() is added. Cross-validate custom model functions.
Bug fix: the control argument in cross_validate() was not being used. Now it is.
In cross_validate(), the model is no longer fitted twice when a warning is thrown during fitting.
Adds metrics argument to cross_validate() and validate(). Allows enabling the regular Accuracy metric in binomial or to disable metrics (will currently still be computed but not included in the output).
AICc is now computed with the MuMIn package instead of the AICcmodavg package, which is no longer a dependency.
Adds lifecycle badges to the function documentation.
evaluate() is added. Evaluate your model’s predictions with the same metrics as used in cross_validate().
Adds 'multinomial' family/type to baseline() and evaluate().
Adds multiclass_probability_tibble() for generating a random probability tibble.
Adds random_effects argument to baseline() for adding random effects to the Gaussian baseline model.
Adds Zenodo DOI for easier citation.
In nested confusion matrices, the Reference column is renamed to Target, to use the same naming scheme as in the nested predictions.
Bug fix: p-values are correctly added to the nested coefficients tibble. Adds tests of this table as well.
Adds extra unit tests to increase code coverage.
When argument "model_verbose" is TRUE, the used model function is now messaged instead of printed.
Adds badges to README, including travis-ci status, AppVeyor status, Codecov, min. required R version, CRAN version and monthly CRAN downloads. Note: Zenodo badge will be added post release.
R v. 3.5Adds optional parallelization.
Results now contain a count of singular fit messages. See ?lme4::isSingular for more information.
Argument "positive" changes default value to 2. Now takes either 1 or 2 (previously 0 and 1). If your dependent variable has values 0 and 1, 1 is now the positive class by default.
AUC calculation has changed. Now explicitly sets the direction in pROC::roc.
Unit tests have been updated for the new random sampling generator in R 3.6.0. They will NOT run previous versions of R.
Adds baseline() for creating baseline evaluations.
Adds reconstruct_formulas() for reconstructing formulas based on model definition columns in the results tibble.
Adds combine_predictors() for generating model formulas from a set of fixed effects.
Adds select_metrics() for quickly selecting the metrics and model definition columns.
Breaking change: Metrics have been rearranged and a few metrics have been added.
Breaking change: Renamed argument folds_col to fold_cols to better fit the new repeated cross-validation option.
New: repeated cross-validation.
Created package :)