- 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
- Breaking: change
generate_mild_df()
to a new interface - Breaking: change
mildsvm()
tomismm()
- Breaking: fix S3 method issue, affects
mi_df
andmild_df
methods parameter - Add
mi_df()
class and methods, includingas_mi_df()
- Add method for
mi_df
objects formisvm()
,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
- Fix bug where NaN columns passed to mildsvm() would fail
- Fix bug where columns with identical values passed to mildsvm() would fail
- 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
- 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.
- 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.