- Fixes bug in
`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 modelâ€™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.

- Unit tests have been made compatible with
`R v. 3.5`

Adds 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 :)