A new set of calibration functions are added that don’t calibrate
the model (called cal_*_none()). These can be used as a
reference implementation when tuning the calibration method
(#174).
A new function bound_prediction() is available to
constrain the values of a numeric prediction (#142).
cal_estimate_linear() and
cal_estimate_logistic() now sets
smooth = FALSE if data contains too few unique observations
for splines to be fit, throwing a warning instead of an error
(#167).
Transition from the magrittr pipe to the base R pipe.
A bug was fixed where cal_estimate_isotonic() always
used a bootstrap sample.
Fixed a bug where non-standard names of class probability estimates resulted in an error for some calibration models (#145).
Bug fix for cal_plot_breaks() with binary
classification with custom probability column names (#144).
Fixed an error in int_conformal_cv() when grouped
resampling was used (#141).
Fixed an issue where the distance metric appeared
inconsistently when using threshold_perf() with custom
metric sets (@jrwinget, #149).
Quick release to remove the base R pipe (to maintain backwards compatibility). # probably 1.0.1
The conformal functions int_conformal_infer_*() were
renamed to int_conformal_*().
predict.int_conformal_cv() now returns a
.pred column that is the average prediction from the
resampled models. The prediction intervals are centered on
these.
Split conformal inference is available using
int_conformal_split() and conformal quantile regression can
be used with int_conformal_quantile().
Copyright holder changed to Posit Software PBC.
A set of calibration tools were added:
cal_plot_*() functions.cal_estimate_*() functions.cal_validate_*() functions.cal_apply() can take a calibration model and apply it
to a set of existing predictions.Possible calibration tools:
Based on the initial PR (#37) by Antonio R. Vargas,
threshold_perf() now accepts a custom metric set
(#25)
Two functions were added to compute prediction intervals for regression models via conformal inference:
int_conformal_infer()int_conformal_infer_cv()Max Kuhn is now the maintainer (#49).
Re-licensed package from GPL-2 to MIT. All copyright holders are RStudio employees and give consent.
Fixed a bug with how make_class_pred() and
make_two_class_pred() validate the levels
argument (#42).
threshold_perf() now has an explicit
event_level argument rather than respecting the now
deprecated yardstick.event_first global option
(#45).
Bumped the minimum required R version to >=3.4.0 to align with the rest of the tidyverse.
Updated to testthat 3e (#44).
class_pred objects are now comparable and will be
ordered by their levels. Equivocal values are generally considered to be
the smallest value when ordering. NA values can be
considered smaller if vec_order(na_value = "smallest") is
used.Suggest the modeldata package, which is where the
lending_club dataset has been moved after being removed
from recipes.
Use testthat::verify_output() on a test expecting a
specific vctrs error to avoid failure on CRAN if that error changes in
the future.
probably has been brought up to date with vctrs 0.2.0. This vctrs update had many function name changes, and required internal refactoring, but there should be minimal external changes.
The one user facing change comes with casting from one
class_pred object to another class_pred, or to
a factor. Where previously a warning would be thrown if
x had levels that did not exist in to, an
error is now generated. This is consistent with the vctrs behavior when
converting from one factor to another.
x <- class_pred(factor("a"))
to <- class_pred(factor("to"))
vec_cast(x, to)
#> Error: Lossy cast from <class_pred> to <class_pred>.
#> Locations: 1A failing test relying on the R 3.6 change to
sample() has been corrected.
An rlang warning in threshold_perf() has been
fixed.
A small R 3.1 issue with vctrs has been fixed.