- Fixed a bug where the grouping for calibration methods was sensitive to the type of the grouping variables (#127).

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:

- 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()`

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.

- Internal cleanup to be more compatible with vctrs 0.3.0.

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: 1`

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.

- First release