probably 1.2.0
CRAN release: 2025-10-16
Add
required_pkgs()methods toint_conformal_cv(),int_conformal_full(),int_conformal_quantile(), andint_conformal_split(). (#190)Add butcher methods to
int_conformal_cv(),int_conformal_full(),int_conformal_quantile(), andint_conformal_split(). (#194)
probably 1.1.0
CRAN release: 2025-05-21
- Significant refactoring of the code underlying the calibration functions. The user-facing APIs have not changed.
New Features
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()andcal_estimate_logistic()now setssmooth = FALSEif 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.
Bug fixes
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
distancemetric appeared inconsistently when usingthreshold_perf()with custom metric sets (@jrwinget, #149).
probably 1.0.3
CRAN release: 2024-02-23
- Fixed a bug where the grouping for calibration methods was sensitive to the type of the grouping variables (#127).
probably 1.0.2
CRAN release: 2023-06-29
Quick release to remove the base R pipe (to maintain backwards compatibility). # probably 1.0.1
The conformal functions
int_conformal_infer_*()were renamed toint_conformal_*().predict.int_conformal_cv()now returns a.predcolumn 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 withint_conformal_quantile().
probably 1.0.0
CRAN release: 2023-06-01
Copyright holder changed to Posit Software PBC.
-
A set of calibration tools were added:
- The need for calibration can be visualized using the collection of
cal_plot_*()functions. - Calibration methods can be estimated with a family of
cal_estimate_*()functions. - To validate the calibrations using resampling, see the
cal_validate_*()functions. -
cal_apply()can take a calibration model and apply it to a set of existing predictions.
- The need for calibration can be visualized using the collection of
-
Possible calibration tools:
- Binary classification methods: logistic regression, isotonic regression, and Beta calibration.
- Multiclass classification: multinomial, isotonic regression, and Beta calibration
- Regression: linear regression, isotonic regression
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()
probably 0.1.0
CRAN release: 2022-08-29
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()andmake_two_class_pred()validate thelevelsargument (#42).threshold_perf()now has an explicitevent_levelargument rather than respecting the now deprecatedyardstick.event_firstglobal 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).
probably 0.0.6
CRAN release: 2020-06-05
-
class_predobjects are now comparable and will be ordered by their levels. Equivocal values are generally considered to be the smallest value when ordering.NAvalues can be considered smaller ifvec_order(na_value = "smallest")is used.
probably 0.0.4
CRAN release: 2020-01-13
Suggest the modeldata package, which is where the
lending_clubdataset 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 0.0.3
CRAN release: 2019-07-07
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_predobject to anotherclass_pred, or to afactor. Where previously a warning would be thrown ifxhad levels that did not exist into, 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: 1
probably 0.0.2
CRAN release: 2019-03-07
Bug fixes
A 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.
