abclass 0.3.0
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 cross-validation procedure
abclass 0.2.0
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
New features
- The first release of abclass providing the
multi-category angle-based large-margin classifiers with various loss
functions.