NEWS
abclass 0.4.1.9010
Minor changes
- Changed the default
alignment to lambda for cv.abclass() and refit in
et.abclass() if a sequence of lambda's is specified. A warning message
would be thrown out for the former.
abclass 0.4.0 (2022-09-18)
New features
- Added support of sparse matrix
x of class sparseMatrix (provided by the
{Matrix} package) for abclass() and predict.abclass().
- Added new functions named
cv.abclass() and et.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() and cv.supclass() for details.
Major Changes
- Simplified the function
abclass() and moved the tuning procedure by
cross-validation to the function cv.abclass().
Minor Changes
- Changed the default values of the following arguments for
abclass.control().
alpha: from 0.5 to 1.0epsilon: from 1e-3 to 1e-4
Bug fixes
- Fixed
alignment in abclass.control().
abclass 0.3.0 (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 to maxit for abclass().
Bug fixes
- Fixed the validation indices in the cross-validation procedure
abclass 0.2.0 (2022-04-12)
New features
- Added experimental group-wise regularization by group lasso penalty.
Minor changes
- Removed the function call from the return of
abclass() to avoid
unnecessarily large returned objects
- Changed the default value of
lum_c for abclass() from 0 to 1.
- Renamed the argument
rel_tol to epsilon for abclass().
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
abclass 0.1.0 (2022-03-07)
New features
- The first release of abclass providing the multi-category angle-based
large-margin classifiers with various loss functions.