Changelog
Source:NEWS.md
abclass 0.4.0
CRAN release: 2022-09-18
New features
- Added support of sparse matrix
x
of classsparseMatrix
(provided by the Matrix package) forabclass()
andpredict.abclass()
. - Added new functions named
cv.abclass()
andet.abclass()
for training and tuning the angle-based classifiers with cross-validation and an efficient tuning procedure for lasso-type algorithms, respectively. See the corresponding function documentation for details. - Added experimental classifiers with sup-norm penalties. See the functions
supclass()
andcv.supclass()
for details.
Major Changes
- Simplified the function
abclass()
and moved the tuning procedure by cross-validation to the functioncv.abclass()
.
Minor Changes
- Changed the default values of the following arguments for
abclass.control()
.-
alpha
: from0.5
to1.0
-
epsilon
: from1e-3
to1e-4
-
Bug fixes
- Fixed
alignment
inabclass.control()
.
abclass 0.3.0
CRAN release: 2022-05-28
New features
- Added experimental group-wise regularization by group SCAD and group MCP penalty.
- Added a new function named
abclass.control()
to specify the control parameters and simplify the main function interface.
Minor changes
- Renamed the argument
max_iter
tomaxit
forabclass()
.
abclass 0.2.0
CRAN release: 2022-04-12
Bug fixes
- Fixed the first derivatives of the boosting loss
- Fixed the label prediction by using the fitted inner products instead of the probability estimates
- Fixed the computation of regularization terms for verbose outputs in
AbclassNet
- Fixed the computation of validation accuracy in cross-validation
- Fixed the assignment of
lum_c
in the associated header files. - Fixed the computation of lower bound for distinct observation weights