Changes in version 0.4.1.9000                      

                 Changes in version 0.4.1 (2025-08-19)                  

  - Fix documentation to address CRAN NOTEs
  - Minor updates to functions, snapshot tests, and Github actions to
    accomodate newer versions of other packages (in particular, dplyr,
    tibble, testthat)

                 Changes in version 0.4.0 (2022-07-14)                  

Add ordinal methods to the package

  - Add omisvm() for ordinal multiple instance support vector machine
  - Add mior() for multiple instance ordinal regression
  - Add misvm_orova() for MI-SVM reducing ordinal to binary one-vs-all
    classification
  - Add svor_exc() for support vector ordinal regression with explicit
    constraints

Other changes

  - Breaking: change generate_mild_df() to a new interface
  - Breaking: change mildsvm() to mismm()
  - Breaking: fix S3 method issue, affects mi_df and mild_df methods
    parameter
  - Add mi_df() class and methods, including as_mi_df()
  - Add method for mi_df objects for misvm(), cv_misvm() and all new
    ordinal methods
  - Add ordmvnorm data for examples
  - Add print methods for kfm_exact, kfm_nystrom, mild_df, mior, misvm,
    mismm, misvm_orova, omisvm, smm, svor_exc
  - Package now depends on R > 3.5.0, new imports of pillar, utils
  - fix warning when misvm() has matrix passed
  - fix .reorder() ambiguity
  - pass lintr checks
  - re-work internals for easier testing

                        Changes in version 0.3.1                        

  - Fix bug where NaN columns passed to mildsvm() would fail
  - Fix bug where columns with identical values passed to mildsvm()
    would fail

                        Changes in version 0.3.0                        

  - Add new method to mildsvm(): method = 'qp-heuristic'. This works
    similar to the method of the same name in misvm(), but uses the SMM
    kernel from kme() in the underlying calculations.
  - Fix bug in classify_bags() when using factors

                        Changes in version 0.2.0                        

  - The main modeling functions (misvm(), mildsvm(), and smm()) now have
    three methods:
      - Formula method (i.e. misvm(mi(y, bags) ~ x1 + x2, data = df,
        ...))
      - Data-frame method (i.e. misvm(x, y, bags, ...))
      - Method for the mild_df class (I.e. misvm(mil_data, ...)). This
        method often performs non-trivial aggregation or transformation
        since misvm() and smm() work naturally on MIL data and
        supervised data, respectively.
  - Prediction on main modeling functions always returns a tibble with a
    single column depending on the type argument
  - Kernel feature maps functions are now organized as kfm_nystrom(),
    kfm_exact() with a build_fm() method.
  - Update MilData class to mild_df class, and improve the class methods
    and constructors.
  - Many internal methods removed and restructured.

                        Changes in version 0.1.0                        

  - Initial release. This release has several known bugs and an early
    input/output scheme that has since been revised. This represents a
    mostly working starting point.