fairmodels 1.2.0
- Added filtering metrics when plotting and printing of
fairness_object
.
- Added ability to add custom measure function to print method of
fairness_object
- Refactored code with tidyverse style
- Changed the order of metrics in
metric_scores
plot to match the ones in fairness_check
- Added instruction for creating custom metric in README
- Added references to vignettes
- Enhanced the advanced vignette
fairmodels 1.1.1
- Fixed error which appeared when 2 fairness objects had the same labels in them. Now if this appears it throws an error. (#41)
privileged
parameter is now converted to character. (#41)
reweight()
function now accepts factors (#41)
fairmodels 1.1.0
- Added function
fairness_check_regression()
that supports regression models along with 2 plot types (#38).
- Added additional tests.
- Modularized
fairness_check()
code.
- Changed x-axis ticks generation in
fairness_check()
.
- Fixed issues with `plot_density
- Updated links in README and DESCRIPTION.
fairmodels 1.0.1
- Changed examples - added parameter
num.threads = 1
to ranger
and added donttest{} to examples with long computation time.
fairmodels 1.0.0
- Added citation information
- Added additional reference in
fairness_check()
documentation.
- Fixed links in DESCRIPTION and README.
fairmodels 0.2.6
- Fixed bug which appeared when two fairness objects were passed to
fairness_check
without an explainer. (#36)
fairmodels 0.2.5
- Extended documentation for
epsilon
parameter in fairness_check()
function.
fairmodels 0.2.4
- Deleted on-load information message about four-fifths rule.
- Fixed bug with
NA
warning in metrics that are not chosen. (#32)
fairmodels 0.2.3
- Fixed the way the
parity_loss
is calculated in all_cutoffs
and ceteris_paribus_cutoff
. (#24)
- Updated vignettes
- changed documentation of functions to explicitly state metrics instead of
fairness_check_metrics()
. (#29)
- Fixed typos (#27 and #28)
- Changed conclusion drawn from density plot in
Basic Tutorial
(#26)
fairmodels 0.2.2
fairness_check_data
now instead of 0
has NA
due to concerns of interpretability - insignificant difference could lead up to maximal value of loss. With that change when NA
is created user will see warning when plotting or printing. This doesn’t affect other objects and plots.
- Description fixes
- Added
metric_scores
plot to basic tutorial
- Updated new documentation in
roc_pivot
fairmodels 0.2.1
- bug related to
fairness check plot
fixed - rectangles did not appear for low epsilon values
fairmodels 0.2.0
- adhering to four-fifths (80%) rule - changed fairness check and parity loss calculation. Now ratio is being calculated instead of differences.(#17)
- Some plots now have default fairness metrics - same as in
fairness_check
stack_metrics
now has parameter fairness_metrics
- corrected vignettes
- enhanced tests
fairmodels 0.1.1
- changed examples in
metric_scores
function
- changed
DALEX
URL in README
- changed pre-processing to preprocessing in DESCRIPTION
fairmodels 0.1.0
- main function
fairness_check()
implemented
- various bias visualization functions implemented
- pre-processing and post-processing bias mitigation techniques implemented
- 2 vignettes present