Unobserved classes and extra variables in high-dimensional discriminant analysis

@article{Fop2021UnobservedCA,
  title={Unobserved classes and extra variables in high-dimensional discriminant analysis},
  author={Michael Fop and Pierre-Alexandre Mattei and Charles Bouveyron and Thomas Brendan Murphy},
  journal={Advances in Data Analysis and Classification},
  year={2021},
  volume={16},
  pages={55 - 92}
}
In supervised classification problems, the test set may contain data points belonging to classes not observed in the learning phase. Moreover, the same units in the test data may be measured on a set of additional variables recorded at a subsequent stage with respect to when the learning sample was collected. In this situation, the classifier built in the learning phase needs to adapt to handle potential unknown classes and the extra dimensions. We introduce a model-based discriminant approach… 
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