tune 0.1.2
Bug Fixes
-
last_fit()
andworkflows::fit()
will now give identical results for the same workflow when the underlying model uses random number generation (#300). -
Fixed an issue where recipe tuning parameters could be randomly matched to the tuning grid incorrectly (#316).
-
last_fit()
no longer accidentally adjusts the random seed (#264). -
Fixed two bugs in the acquisition function calculations.
Other Changes
-
New
parallel_over
control argument to adjust the parallel processing method that tune uses. -
The
.config
column that appears in the returned tibble from tuning and fitting resamples has changed slightly. It is now always of the form"Preprocessor<i>_Model<j>"
. -
predict()
can now be called on the workflow returned fromlast_fit()
(#294, #295, #296). -
tune now supports setting the
event_level
option from yardstick through the control objects (i.e.control_grid(event_level = "second")
) (#240, #249). -
tune now supports workflows created with the new
workflows::add_variables()
preprocessor. -
Better control the random number streams in parallel for
tune_grid()
andfit_resamples()
(#11) -
Allow
...
to pass options fromtune_bayes()
toGPfit::GP_fit()
. -
Additional checks are done for the initial grid that is given to
tune_bayes()
. If the initial grid is small relative to the number of model terms, a warning is issued. If the grid is a single point, an error occurs. (#269) -
Formatting of some messages created by
tune_bayes()
now respect the width and wrap lines using the newmessage_wrap()
function. -
tune functions (
tune_grid()
,tune_bayes()
, etc) will now error if a model specification or model workflow are given as the first argument (the soft deprecation period is over). -
An
augment()
method was added for objects generated bytune_*()
,fit_resamples()
, andlast_fit()
.