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v0.4.0

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

v0.3.1

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

v0.3.0

• 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

v0.2.0

• 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.

v0.1.0

• 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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.