- Extended GUI (still incomplete)
- Added radiobiological/ML outcome model-based components
- Grouped components into conventional, ML and radiobiological (via superclasses)
- Added data-medoid initialization
- Added constraint support for trust-constr and NSGA-3
- Re-implemented PyPop7 wrapper
- Refined code/style/documentation for the full package
- Replaced head-and-neck example with TG-119 (by this, Git LFS can be removed due to the smaller file sizes)
- Adapted ML model classes to account for the changes in the tabular data generator