abclass 0.4.0

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 1.0
  • epsilon: from 1e-3 to 1e-4

Bug fixes

• Fixed alignment in abclass.control().