aorsf 0.0.8
- Fixed an issue where an uninformative error message would occur when
pred_horizon
was > max(time) fororsf_summarize_uni
. Thanks to @JyHao1 and @DustinMLong for finding this!
aorsf 0.0.7
CRAN release: 2023-01-12
- Additional changes in internal testing to avoid problems with ATLAS
aorsf 0.0.6
CRAN release: 2023-01-06
- Minor fix for internal tests that were failing when run on ATLAS
aorsf 0.0.5
CRAN release: 2022-12-14
orsf()
no longer throws errors or warnings when you try to give it a single predictor. A note was added to the documentation in the details of?orsf
that explains why using a single predictor withorsf()
is somewhat useless. This was done to resolve https://github.com/mlr-org/mlr3extralearners/issues/259.predict.orsf_fit
now acceptspred_horizon = 0
and returns sensible values. Thanks to @mattwarkentin for the feature request.added a function to perform variable selection,
orsf_vs()
.Made variable importance consistent with respect to
group_factors
. Originally, the output fromorsf
would have ungrouped VI values whileorsf_vi
would have grouped values. With this update,orsf
defaults to grouped values. The ungrouped values can still be recovered.Fixed an issue in
orsf_pd
functions where output data were not being returned on the original scale.
aorsf 0.0.4
CRAN release: 2022-11-07
orsf
formulas now acceptsSurv
objects (see https://github.com/ropensci/aorsf/issues/11)Added
verbose_progress
input toorsf
, which prints messages to console indicating progress.Allowance of missing values for
orsf
. Mean and mode imputation is performed for observations with missing data. These values can also be used to impute new data with missing values.Centering and scaling of predictors is now done prior to growing the forest.
aorsf 0.0.3
CRAN release: 2022-10-09
Included rOpenSci reviewers Christopher Jackson, Marvin N Wright, and Lukas Burk in
DESCRIPTION
as reviewers. Thank you!Added clarification to docs about pros/cons of different variable importance techniques
Added regression tests for
aorsf
versusobliqueRSF
(they should be similar)Additional support and tests for functions with long right hand sides
Updated out-of-bag vignette with more appropriate custom functions.
Allow status values in input data to be more general, i.e., not just 0 and 1.
Allow missing values in
predict
functions, including partial dependence.
aorsf 0.0.2
CRAN release: 2022-09-05
- Modified unit tests for compatibility with extra checks run through CRAN.
aorsf 0.0.1
CRAN release: 2022-08-23
Added
orsf_control_custom()
, which allows users to submit custom functions for identifying linear combinations of inputs while growing oblique decision trees.Added
weights
input toorsf
, allowing users to over or under fitorsf
to specific data in their training set.Added
chf
andmort
options topredict.orsf_fit()
. Mortality predictions are not fully implemented yet - they are not supported in partial dependence or out-of-bag error estimates. These features will be added in a future update.