NEWS
mildsvm 0.4.1.9000
mildsvm 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)
mildsvm 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
mildsvm 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
mildsvm 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
mildsvm 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.
mildsvm 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.